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NUTRITION AND METABOLISM
Nutrition and Health
Adrianne Bendich, PhD, FACN, Series Editor
For other titles published in this series, go to
www.springer.com/series/7659
NUTRITION
AND METABOLISM
Underlying Mechanisms
and Clinical Consequences
Editor
Christos S. Mantzoros, MD, DSc
Division of Endocrinology, Diabetes and Metabolism,
Beth Israel Deaconess Medical Center, Harvard Medical School,
Boston, MA, USA
Editor
Christos S. Mantzoros, MD, DSc
Division of Endocrinology
Diabetes and Metabolism
Beth Israel Deaconess Medical Center
Harvard Medical School
Boston, MA
USA
Series Editor
Adrianne Bendich, PhD, FACN
GlaxoSmithKline Consumer Healthcare
Parsippany, NJ
USA
ISBN: 978-1-60327-452-4 e-ISBN: 978-1-60327-453-1
DOI: 10.1007/978-1-60327-453-1
Library of Congress Control Number: 2009922619
© Humana Press, a part of Springer Science+Business Media, LLC 2009
All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the
publisher (Humana Press, c/o Springer Science + Business Media, LLC, 233 Spring Street, New York, NY 10013, USA),
except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of informa-
tion storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known
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While the advice and information in this book are believed to be true and accurate at the date of going to press, neither the
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The publisher makes no warranty, express or implied, with respect to the material contained herein.
Printed on acid-free paper
springer.com
Dedication
To my parents, whose lifelong service to their suffering fellow human beings became
a true inspiration and enlightened guidance for my professional and personal life
Series Preface
The Nutrition and HealthTM series of books have, as an overriding mission, to pro-
vide health professionals with texts that are considered essential because each includes:
(1) a synthesis of the state of the science, (2) timely, in-depth reviews by the leading
researchers in their respective fields, (3) extensive, up-to-date fully annotated reference
lists, (4) a detailed index, (5) relevant tables and figures, (6) identification of paradigm
shifts and the consequences, (7) virtually no overlap of information between chapters,
but targeted, inter-chapter referrals, (8) suggestions of areas for future research, and
(9) balanced, data-driven answers to patient/health professionals questions which are
based upon the totality of evidence rather than the findings of any single study.
The series volumes are developed to provide valuable in-depth information to nutrition
health professionals and health providers interested in practical guidelines. Each editor
has the potential to examine a chosen area with a broad perspective, both in subject mat-
ter as well as in the choice of chapter authors. The international perspective, especially
with regard to public health initiatives, is emphasized where appropriate. The editors,
whose trainings are both research and practice oriented, have the opportunity to develop
a primary objective for their book, define the scope and focus, and then invite the leading
authorities from around the world to be part of their initiative. The authors are encouraged
to provide an overview of the field, discuss their own research, and relate the research
findings to potential human health consequences. Because each book is developed de
novo, the chapters are coordinated so that the resulting volume imparts greater knowledge
than the sum of the information contained in the individual chapters.
Nutrition and Metabolism: Underlying Mechanisms and Clinical Consequences, edited
by Christos S. Mantzoros, MD is a very welcome addition to the Nutrition and Health
Series and fully exemplifies the Series’ goals. This volume is especially timely since
the obesity epidemic continues to increase around the world and the comorbidities, such
as the metabolic syndrome, type II diabetes, hypertension, and hyperlipidemia are seen
even in very young children. The editor reminds us that, for most people, their weight
remains relatively stable despite wide variations in the types of foods we consume each
day, differences in caloric content, and differences in daily physical activity. It is only
recently that physicians, scientists, and health providers have begun to think about the
complexities of excess body weight. This volume contains informative chapters that
look at the genetics associated with obesity, the role of the nervous system and the
endocrine system, the gastrointestinal tract and of great importance, adipose tissue,
as more than a fat storage site. The last decade has seen an explosion of identification
vii
viii Series Preface
and characterization of the many bioactive molecules that are synthesized and secreted
by adipose cells (adipokines). The adipokines and other molecules synthesized in the
stomach, intestines, pancreas, and other gastrointestinal organs have been associated
with the development of obesity and its comorbidities as well as many, often thought of
as unrelated, consequences including insulin resistance, cardiovascular complications,
lipid disorders, hypertension, and hormonal imbalances as examples. Thus, the relevance
of obesity-related pathophysiology to the clinical setting is of great interest to not only
academic researchers, but also healthcare providers. This text is the first to synthesize
the knowledge base concerning obesity and its comorbidities including metabolic syn-
drome, diabetes, hypertension, and hyperlipidemia, and relate these to the mechanisms
behind the alterations in metabolism that increase chronic disease risk. This unique
volume also contains practice guidelines and tools for obesity management to help the
practicing health professional as well as those professionals who have an interest in the
latest, up-to-date information on obesity treatments and their implications for improving
human health and reducing obesity-related diseases.
This volume serves the dual purposes of providing current clinical assessment and
management guidelines as well as relevant background information on the genetics and
pathophysiology associated with the consequences of obesity. The chapters include an
historic perspective as well as suggestions for future research opportunities. Dr. Mant-
zoros is an internationally recognized leader in the field of obesity research as well as
clinical outcomes. He and his authors are excellent communicators and he has worked
tirelessly to develop a book that is destined to be the benchmark in the field because
of its extensive, in-depth chapters covering the most important aspects of the complex
interactions between cellular functions, diet and obesity, and its impact on disease states.
The editor has chosen 32 of the most well-recognized and respected authors from around
the world to contribute the 18 informative chapters in the volume. Hallmarks of all of the
chapters include complete definitions of terms with the abbreviations fully defined for the
reader and consistent use of terms between chapters. Key features of this comprehensive
volume include the informative key points and keywords that are at the beginning of each
chapter, appendices that include detailed tables of major nutrient recommendations for
weight reduction in the obese as well as for those with diabetes; detailed descriptions
of the Dietary Approaches to Stop Hypertension (DASH) diet protocol; an extensive list
of foods and their glycemic index and many other practical guidelines to help in patient
management. The volume also contains more than 80 detailed tables and informative
figures, an extensive, detailed index, and more than 2,000 up-to-date references that
provide the reader with excellent sources of worthwhile information about the role of
diet, exercise, food intake, physiology and pathophysiology of obesity, the metabolic
syndrome, types I and II diabetes, and other obesity-related comorbidities.
Dr. Mantzoros has coauthored many of the chapters and he has chosen chapter authors
who are internationally distinguished researchers, clinicians, and epidemiologists who
provide a comprehensive foundation for understanding the role of weight control in the
maintenance of human health as well as its role in obesity and related co-morbidities.
The book is organized into logical sections that provide the reader with an overview of
the complexities of weight control. There is an extensive discussion of the genetics of
obesity and the involvement of at least 11 human genes in the control of food intake and
metabolism. Genetically linked obesity syndromes are described including Prader–Willi
Series Preface ix
syndrome. This chapter includes new information on the genetics of metabolic syndrome,
types I and II diabetes and reviews the findings that link these diseases genetically. The
interaction between the central and peripheral nervous systems, the endocrine system, and
molecules synthesized during digestion are discussed in the next chapter that introduces
the reader to the concepts of metabolic signals, orosensory stimuli, GI tract peptides
and adipokines from fat tissue. Explanations are provided for the role of leptin, insulin,
peptide YY, ghrelin, visfatin, cholecystokinin, and many other important modulators
in human metabolism. An important chapter is devoted to the description of the central
nervous system with detailed explanations of the importance of the hypothalamus and
the brain stem. We learn that control of appetite resides in the arcuate nucleus area of the
hypothalamus, whereas the paraventricular nucleus is involved with energy homeostasis.
This chapter reviews the importance of orexigenic and anorexigenic neuropeptides as
well as the effects of thyroid hormones, adrenergic receptors, and thermogenic tissues.
The final chapter in the section on genetics and pathophysiology looks at insulin resis-
tance and its consequences. The concept of adipose tissue inflammation is introduced
and there is discussion about body fat distribution including the effects of visceral vs.
subcutaneous fat.
Childhood obesity is a major public health concern as the percentage of young children
that are obese or overweight continues to grow globally. There is an extensive review of the
published studies that have attempted to control weight gain in children and adolescents
most of which do not use pharmacological agents. Certainly, more research is needed in
this area as long-term successful strategies have not been developed and well-accepted
guidelines for clinical practice are not currently available. Two chapters review recom-
mendations for diet and physical activity for healthy adults in one chapter and for the
prevention and management of diabetes in the other chapter. These chapters discuss the
importance of reducing trans fats, total fat, refined grains, and sugar-sweetened bever-
ages. The authors review the data on the importance of physical activity to help control
lipid levels and improve energy balance. The final chapter in this section examines
the association of obesity and cancer risk. Poor dietary habits account for about 35%
of incident cancers and smoking accounts for 30%; obesity accounts for 15%. About
16–20% of cancer deaths in US women and 14% in US men can be attributed to obesity.
The chapter includes an analysis of the dietary habits around the globe that can result in
a sevenfold difference in the rates of breast and prostate cancers between Western type
diets and the rates seen in Japan.
Many nations have developed nutrition recommendations for the general population as
well as for those individuals who suffer from the co-morbidities associated with obesity
including diabetes and cardiovascular disease. This section of the volume considers the
guidance that has been provided, reviews the history of the development of US national
dietary guidelines and the most recent Food Guide Pyramid, and follows with a provoca-
tive chapter by Drs. Willett and Stampfer that questions the scientific basis for some
of the more general national recommendations given in the Pyramid. Nutrition recom-
mendation for those with cardiovascular disease includes reduction of salt, saturated and
trans fats and increases in dietary fiber, antioxidants, B vitamins, omega-3 fatty acids,
mono-unsaturated fatty acids, calcium, and potassium. Examples of food-based interven-
tion studies that have reduced cardiovascular disease (CVD) risk factors including the
prudent diet, DASH diet, Mediterranean diet and the guidelines from the American Heart
x Series Preface
Association and the European Society of Cardiology are discussed in detail. Details are
also provided for the assessment of cardiovascular disease including the biochemical
markers currently used to stage the patient. This chapter also discussed the role of dietary
supplements in CVD management. In the past 20 years, a new field of patient care has
emerged called medical nutrition therapy (MNT). MNT has been particularly important
in the management of patients with types I and II diabetes. Practice guidelines have been
developed for children, adolescents, and adults and have been of value in the control of
blood glucose levels as well as glycosylated hemoglobin. Diets are recommended that
contain levels of essential micronutrients important to the diabetic. This chapter and the
additional information in the related appendices provide practical information for the
health provider. There is also a separate chapter that describes the Mediterranean diet
and the clinical studies, including survey data, case–control and intervention studies that
have examined the potential for this diet to reduce obesity and CVD.
The final section includes in-depth chapters on the clinical assessment and manage-
ment of obesity and its co-morbidities. There is a comprehensive chapter on lifestyle
and pharmacological treatments for obesity. It is of interest that even today that hyper-
cholesterolemia remains undiagnosed in 50% of the US population and 95% remain
undertreated. This chapter explains the effects of hypertension, often seen in the obese,
on carotid medial intimal thickness and the clinical studies that have included treat-
ments. A comprehensive review of statin use is also included. Accurate diagnosis tools
for obesity and diabetes are provided in the next chapter and also include management
tools for gestational diabetes. Another informative chapter describes the use of bariatric
surgery and the critical importance of the preoperation evaluation. We are reminded that
to date weight loss surgery is the only effective treatment for severe, medically com-
plicated, and refractory obesity. Guidelines for patient inclusion, types of operations,
and importantly, postoperation care are provided in detail. The final chapter reviews the
major co-morbidities associated with obesity and weight loss due to bariatric surgery
that have not been included in other chapters. These areas include the increased risk of
osteoporosis and fracture following bariatric surgery and the increased risk of gallstones
that also occurs after this surgery. On the other hand, there appears to be a significant
decrease in mortality as well as a decrease in sleep apnea and osteoarthritis. The lit-
erature on the increased risk of certain cancers with obesity is also included. Each of
the chapter authors has integrated the newest research findings so the reader can better
understand the complex interactions that can result from excess weight gain as well as
loss of excess weight.
Given the growing concern with the increase in adult as well as childhood obesity, it
is not surprising to find that all chapters in this valuable book are devoted to the clinical
aspects of obesity, weight control, diabetes, and other chronic diseases associated with
obesity. Moreover, both the cultural aspects of weight gain and the emotional triggers
of eating are reviewed. Emphasis is also given to the growing awareness that obesity is
associated with a low-grade inflammatory state. The editor and authors have integrated
the information within these chapters so that the healthcare practitioner can provide guid-
ance to the patient about the potential consequences of chronic obesity. The inclusion of
both the earlier chapters on the complexity of human physiology and the chapters that
contain clinical discussions helps the reader to have a broader basis of understanding
of obesity and the attendant co-morbidities.
Series Preface xi
In conclusion, Nutrition and Metabolism: Underlying Mechanisms and Clinical Con-
sequences, edited by Christos S. Mantzoros, MD provides health professionals in many
areas of research and practice with the most up-to-date, well-referenced volume on the
importance of maintaining normal weight so that obesity and the obesity-related chronic
diseases that can adversely affect human health are avoided. This volume will serve the
reader as the benchmark in this complex area of interrelationships between body weight,
the central nervous system, endocrine organs, the GI tract, the biochemical reactions in
fat cells, inflammation of adipose tissue, and the functioning of all other organ systems
in the human body. Moreover, the interactions between obesity, genetic factors, and the
numerous co-morbidities are clearly delineated so that students as well as practitioners
can better understand the complexities of these interactions. Dr. Mantzoros is applauded
for his efforts to develop the most authoritative resource in the field to date and this
excellent text is a very welcome addition to the Nutrition and Health series.
Adrianne Bendich, PhD, FACN
Parsippany, NJ
Preface
Research on obesity spans a wide range of disciplines, from molecular biology to
physiology to epidemiology and translational research to clinical medicine. This book
attempts to review comprehensively, for practicing clinicians and scientists alike, our
current understanding of how nutrition interacts with the genetic substrate as well as
environmental-exogenous factors, including physical activity or the lack thereof, to
result in insulin resistance and the metabolic syndrome. Furthermore, the causation,
epidemiology, clinical presentation, prevention, and treatment of the most common
manifestations of disease states associated with the metabolic syndrome are reviewed.
After presenting the Scope of the Problem, the first major part of the book is devoted to
Genetics and Pathophysiology, the second part of the book presents the Public Health
Perspective of the most prevalent problems associated with nutrition and the metabolic
syndrome, whereas the third major part of the book focuses on Clinical Assessment
and Management of the main disease states associated with inappropriate nutrition and
the metabolic syndrome. Finally, general information useful for both clinicians and
researchers alike is presented in the Appendix.
Covering the entire field of nutrition or metabolism would have been a daunting task,
far beyond the scope of a single volume book. Thus, Nutrition and Metabolism: Underly-
ing Mechanisms and Clinical Consequences offers only an up-to-date and authoritative
review of the major scientific and clinical aspects of the overlapping areas between
nutrition and metabolism. I am indebted to all my colleagues, most of them scientists
and distinguished professors at Harvard University, for their valuable contributions.
I thank the staff at Humana Press for their hard work in putting together this book in
close collaboration with staff in my group, especially Lauren Kuhn and Jess Fargnoli.
We also wish to express our gratitude to Dr. Adrianne Bendich, the Series Editor, for
her thoughtful suggestions.
I certainly hope that the efforts of all of us will not only provide much needed in-
formation to our practicing colleagues but also serve as a stimulus for further research
in this scientific topic of utmost importance for the developed world in the twenty-first
century. Our mission will be eventually accomplished if, through higher quality research,
superior teaching, and consequently improved health services, the quality of our preven-
tion programs as well as the quality of health care we provide to our suffering fellow
human beings is ultimately enhanced.
Christos S. Mantzoros
Boston, MA
xiii
Contents
Series Preface .......................................................................................................... vii
Preface..................................................................................................................... xiii
Contributors ............................................................................................................ xix
Part I Scope of the Problem
1 Nutrition and the Metabolic Syndrome: A Twenty-First-Century
Epidemic of Obesity and Eating Disorders..................................................... 3
Christos S. Mantzoros
Part II Genetics and Pathophysiology
2 Genes and Gene–Environment Interactions in the Pathogenesis
of Obesity and the Metabolic Syndrome ........................................................ 11
Despina Sanoudou, Elizabeth Vafiadaki,
and Christos S. Mantzoros
3 Environmental Inputs, Intake of Nutrients, and Endogenous
Molecules Contributing to the Regulation of Energy Homeostasis................ 41
Theodore Kelesidis, Iosif Kelesidis, and Christos S. Mantzoros
4 Central Integration of Environmental and Endogenous
Signals Important in the Regulation of Food Intake
and Energy Expenditure .................................................................................. 77
Iosif Kelesidis, Theodore Kelesidis, and Christos S. Mantzoros
5 Insulin Resistance in States of Energy Excess:
Underlying Pathophysiological Concepts ....................................................... 107
Susann Blüher and Christos S. Mantzoros
Part III Public Health Perspective
6 Targeting Childhood Obesity Through Lifestyle Modification ...................... 125
Eirini Bathrellou and Mary Yannakoulia
7 Diet and Physical Activity in the Prevention of Obesity ................................ 135
Frank B. Hu
xv
xvi Contents
8 Diet and Exercise in the Prevention and Management
of the Metabolic Syndrome............................................................................. 149
Mary Yannakoulia, Evaggelia Fappa, Janice Jin Hwang,
and Christos S. Mantzoros
9 Diet and Physical Activity in Cancer Prevention............................................ 161
Alicja Wolk
Part IV Nutrition Recommendations
10 Food Guide Pyramids and the 2005 MyPyramid............................................ 195
Jessica Fargnoli and Christos S. Mantzoros
11 Nutrition Recommendations for the General Population:
Where Is the Science? ..................................................................................... 209
Walter C. Willett and Meir J. Stampfer
12 Nutrition Recommendations and Interventions for
Subjects with Cardiovascular Disease ............................................................ 221
Meropi Kontogianni, Mary Yannakoulia, Lauren Kuhn,
Sunali Shah, Kristina Day, and Christos S. Mantzoros
13 Medical Nutrition Therapy in the Treatment of
Type 1 and Type 2 Diabetes ............................................................................ 245
Olga Kordonouri, Caroline Apovian, Lauren Kuhn,
Thomas Danne, and Christos S. Mantzoros
Part V Clinical Assessment and Management
14 Mediterranean Diet in Disease Prevention: Current Perspectives .................. 263
Jessica Fargnoli, Yoon Kim, and Christos S. Mantzoros
15 Lifestyle and Pharmacology Approaches for the
Treatment of Hypertension and Hyperlipidemia ............................................ 279
Peter Oettgen
16 Diagnosis, Evaluation, and Medical Management of
Obesity and Diabetes ...................................................................................... 289
Jean L. Chan and Christos S. Mantzoros
17 Surgical Management of Obesity and Postoperative Care.............................. 329
George L. Blackburn, Torsten Olbers, Benjamin E. Schneider,
Vivian M. Sanchez, Aoife Brennan, Christos S. Mantzoros,
and Daniel B. Jones
Contents xvii
18 Long-Term Impact of Weight Loss on Obesity and
Obesity-Associated Comorbidities ................................................................. 347
Janice Jin Hwang, George Blackburn, and Christos S. Mantzoros
Part VI Appendix
19 Methods for Classifying, Diagnosing, and Monitoring Obesity ..................... 371
Christos S. Mantzoros
20 Methods for Classifying, Diagnosing, and Monitoring Type II Diabetes ....... 385
Christos S. Mantzoros
21 Major Nutrition Recommendations and Interventions
for Subjects with Hyperlipidemia, Hypertension, and/or Diabetes ................ 393
Christos S. Mantzoros
Part VII Resources
Resources ................................................................................................................ 407
Index ....................................................................................................................... 415
Contributors
Caroline Apovian, MD • Division of Endocrinology, Diabetes, and Nutrition,
Boston University School of Medicine and Boston Medical Center, Boston,
MA, USA
Eirini Bathrellou, MSc • Department of Nutrition and Dietetics,
Harokopio University, Athens, Greece
George L. Blackburn, PhD, MD • Division of Nutrition, Beth Israel Deaconess
Medical Center, Harvard Medical School, Boston, MA, USA
Susann Blüher, MD • Hospital for Children and Adolescents, University of Leipzig,
Leipzig, Germany and Division of Endocrinology, Diabetes & Metabolism,
Beth Israel Deaconess Medical Center, Boston, MA, USA
Aoife Brennan, MD • Division of Endocrinology, Diabetes & Metabolism,
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
Jean L. Chan, MD • Division of Endocrinology, Diabetes & Metabolism,
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
Thomas Danne, MD • Diabetes Center for Children and Adolescents,
Childrens’ Hospital at the Bult, Hannover, Germany
Kristina Day, RD • Division of Surgery, Beth Israel Deaconess Medical Center,
Harvard Medical School, Boston, MA, USA
Cara B. Ebbeling, PhD • Children’s Hospital Boston, Harvard Medical School,
Boston, MA, USA
Evaggelia Fappa, MSc • Department of Nutrition and Dietetics,
Harokopio University, Athens, Greece
Jessica Fargnoli, BS • Division of Endocrinology, Diabetes & Metabolism,
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
MA, USA
Frank B. Hu, PhD, MD • Department of Nutrition, Harvard School of PublicHealth,
Boston, MA, USA
Janice Jin Hwang, MD • Division of Endocrinology, Diabetes & Metabolism,
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
MA, USA
xix
xx Contributors
Daniel B. Jones MD, MS • Section of Minimally Invasive Surgery,
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
MA, USA
Iosif Kelesidis, MD • Division of Endocrinology, Diabetes & Metabolism,
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
Theodore Kelesidis, MD • Division of Endocrinology, Diabetes & Metabolism,
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
Yoon Kim, MD • Division of Endocrinology, Diabetes & Metabolism, Beth Israel
Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
Meropi Kontogianni, MD • Department of Nutrition and Dietetics,
Harokopio University, Athens, Greece
Olga Kordonouri, MD • Diabetes Center for Children and Adolescents,
Childrens’ Hospital at the Bult, Hannover, Germany
Lauren Kuhn, BS • Division of Endocrinology, Diabetes & Metabolism,
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
MA, USA
Christos S. Mantzoros, MD, DSc • Division of Endocrinology,
Diabetes & Metabolism, Beth Israel Deaconess Medical Center,
Harvard Medical School, Boston, MA, USA
J. Peter Oettgen, MD • Division of Cardiology, Beth Israel Deaconess
Medical Center, Harvard Medical School, Boston, MA, USA
Torsten Olbers, MD, PhD • Department of Surgery and Gastro Research,
Sahlgrenska University Hospital, Goteborg, Sweden
Deanna Olenczuk, BS • Division of Endocrinology, Diabetes & Metabolism,
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
MA, USA
Vivian M. Sanchez, MD • Section of Minimally Invasive Surgery, Beth Israel
Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
Despina Sanoudou, PhD • Division of Molecular Biology, Foundation
for Biomedical Research of the Academy of Athens, Athens, Greece
Benjamin E. Schneider, MD • Section of Minimally Invasive Surgery,
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
MA, USA
Sunali Shah, BS • Division of Endocrinology, Diabetes & Metabolism,
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
MA, USA
Meir Stampfer, MD • Departments of Nutrition and Epidemiology,
Harvard School of Public Health, Boston, MA, USA
Elizabeth Vafiadaki, PhD • Division of Molecular Biology, Foundation
for Biomedical Research of the Academy of Athens, Athens, Greece
Walter Willett, MD • Department of Nutrition, Harvard School of Public Health,
Boston, MA, USA
Alicja Wolk, DMSc • Institute of Environmental Medicine, Karolinska Institutet,
Stockholm, Sweden
Mary Yannakoulia, PhD • Department of Nutrition and Dietetics,
Harokopio University, Athens, Greece
Resources
1. INTRODUCTION
Inappropriate nutrition, increased calorie intake, and lack of exercise usually lead to
obesity and the metabolic syndrome, which, in turn, are responsible for several chronic
diseases that affect every aspect of a person s life. In addition to prevention and medical
treatment, education is the single most important tool for their management. Education
is also of major importance in raising public health awareness since it can hopefully help
curb the global epidemic of obesity, diabetes, and other disease states associated with
the metabolic syndrome.
Following is a list of government agencies and nongovernmental organizations that
provide information and resources related to nutrition, obesity, and diabetes.
2. DIABETES ORGANIZATIONS
American Association of Diabetes Educators (AADE)
100 West Monroe, Suite 400
Chicago, IL 60603
Tel: 800-338-3633 or 312-424-2426
Fax: 312-424-2427
Diabetes Educator Access Line: 800-TEAMUP4 (800-832-6874)
Email: aade@aadenet.org
Internet: http://www.diabeteseducator.org
American Diabetes Association (ADA)
1701 North Beauregard Street
Alexandria, VA 22311
Tel: 800-DIABETES (800-342-2383)
Fax: 703-549-6995
Email: askada@diabetes.org
Internet: http://www.diabetes.org
407
408 Resources
American Podiatric Medical Association (APMA)
9312 Old Georgetown Road
Bethesda, MD 20814-1621
Foot Care Information Center: 800-FOOT-CARE (800-366-8227)
Tel: 301-581-9200
Fax: 301-530-2752
Email: askapma@apma.org
Internet: http://www.apma.org
Diabetes Exercise and Sports Association (DESA)
8001 Montcastle Drive
Nashville, TN 37221
Tel: 800-898-4322
Fax: 602-433-9331
Email: desa@diabetes-exercise.org
Internet: http://www.diabetes-exercise.org
Joslin Diabetes Center
One Joslin Place
Boston, MA 02215
Tel: 800-JOSLIN-1 or 617-732-2400
Internet: http://www.joslin.org
Juvenile Diabetes Research Foundation International (JDRF)
120 Wall Street
New York, NY 10005-4001
Tel: 800-533-CURE (2873)
Fax: 212-785-9595
Email: info@jdrf.org
Internet: http://www.jdf.org
International Diabetic Federation (IDF)
Avenue Emile De Mot 19 – B-1000
Brussels, Belgium
Tel: +32-2-538-55-11
Fax: +32-2-538-51-14
Email: info@idf.org
Internet: http://www.idf.org
Centers for Disease Control and Prevention (CDC)
National Center for Chronic Disease Prevention and Health Promotion
Division of Diabetes Translation
P.O. Box 8728
Silver Spring, MD 20910
Tel: 877-CDC-DIAB (877-232-3422)
Resources 409
Fax: 301-562-1050
Email: diabetes@cdc.gov
Internet: http://www.cdc.gov/diabetes
3. OBESITY ORGANIZATIONS
Academy for Eating Disorders (AED)
60 Revere Drive, Suite 500
Northbrook, IL 60062
Tel: 847-498-4274
Fax: 847-480-9282
Email: aed@aedweb.org
Internet: http://www.aedweb.org
American Obesity Association (AOA)
1250 24th Street, NW
Suite 300
Washington, DC 20037
Tel: 202-776-7711
Fax: 202-776-7712
Internet: http://www.obesity.org
American Society for Bariatric Surgery (ASBS)
100 SW 75th Street
Suite 201
Gainesville, FL 32607
Tel: 352-331-4900
Fax: 352-331-4975
Email: info@asbs.org
Internet: http://www.asbs.org
American Society of Bariatric Physicians (ASBP)
2821 S. Parker Rd., Ste. 625
Aurora, CO 80014
Tel: 303-770-2526
Fax: 303-779-4834
Email: info@asbp.org
Internet: http://www.asbp.org
International Association for the Study of Obesity (IASO)
231 North Gower Street, London NW1 2NS, UK
Tel: +44-20-7691-1900
Fax: +44-20-7387-6033
Email: inquiries@iaso.org/obesity@iotf.org
Internet: http://www.iaso.org/http://www.iotf.org
410 Resources
North American Association for the Study of Obesity (NAASO)
8630 Fenton Street, Suite 918
Silver Spring, MD 20910
Tel: 301-563-6526
Fax: 301-563-6595
Internet: http://www.naaso.org
4. NUTRITION
American Society for Nutrition (ASN)
9650 Rockville Pike
Suite L-5500
Bethesda, MD 20814
Tel: 301-634-7050
Fax: 301-634-7892
Email: sec@nutrition.org
Internet: http://www.nutrition.org
United States Department of Agriculture (USDA) Center
for Nutrition Policy and Promotion
3101 Park Center Drive
Room 1034
Alexandria, VA 22302-1594
Tel: 1-888-7pyramid
Email: support@cnpp.usda.gov
Internet: http://www.mypyramid.gov
Harvard School of Public Health (HSPH) Department of Nutrition
665 Huntington Avenue
Boston, MA 02115
Tel: 617-432-1851
Fax: 617-432-2435
Email: cstover@hsph.harvard.edu
Internet: http://www.hsph.harvard.edu/academics/nutr
World Health Organization (WHO) Department of Nutrition for Health
and Development
Avenue Appia 20
1211 Geneva 27
Switzerland
Fax: +41-22-791-41-56
Email: nutrition@who.int
Internet: http://www.who.int/nutrition
National Health Information Center
P.O. Box 1133
Washington, DC 20013-1133
Resources 411
Tel: 800-336-4797
Email: info@nhic.org
Internet: http://www.healthierus.gov
Aristides Daskalopoulos Foundation (IAD)
10, Ziridi str
Maroussi 15123, Greece
Tel: +30-211-3494101
Fax: +30-211-3494128
Email: infor@iad.gr
Internet: http://www.iad.gr
American Society for Parenteral and Enteral Nutrition (ASPEN)
8630 Fenton Street, Suite 412
Silver Spring, MD 20910
Tel: 800-727-4567 or 301-587-6315
Fax: 301-587-2365
Email: aspen@nutr.org
Internet: http://www.nutritioncare.org
Dietary Guidelines for Americans
U.S. Department of Agriculture and U.S. Department of Health and Human Serv-
ices
Internet: http://www.health.gov/dietaryguidelines
U.S. Food and Drug Administration (FDA)
Office of Consumer Affairs
5600 Fishers Lane
Rockville, MD 20857
Tel: 888-INFO-FDA (463-6332) and 888-SAFE FOOD (888-723-3366) (Food Infor-
mation Line)
Fax: 301-443-9767
Internet: http://www.fda.gov
Food and Nutrition Information Center (FNIC)
USDA/ARS/National Agricultural Library
10301 Baltimore Avenue, Room 105
Beltsville, MD 20705-2351
Tel: 301-504-5719; TTY: 301-504-6856
Fax: 301-504-6409
Email: fnic@nal.usda.gov
Internet: http://www.nal.usda.gov/fnic
U.S. Department of Agriculture (USDA)
1400 Independence Ave., SW
Washington, DC 20250
412 Resources
Tel: 800-727-9540 and 202-720-2791
Internet: http://www.usda.gov
U.S. Government’s Food Safety Web Site
http://www.foodsafety.gov
5. ORGANIZATIONS OF COMMON INTEREST
American Academy of Pediatrics (AAP)
141 Northwest Point Boulevard
Elk Grove Village, IL 60007-1098
Tel: 847-434-4000 or 888-227-1770
Email: csc@aap.org
Internet: http://www.aap.org
American Association of Clinical Endocrinologists (AACE)
1000 Riverside Avenue
Suite 205, Jacksonville, FL 32204
Tel: 904-353-7878
Fax: 904-353-8185
Email: info@aace.com
Internet: http://www.aace.com
American Dietetic Association (ADA)
120 South Riverside Plaza, Suite 2000
Chicago, IL 60606-6995
Tel: 800-366-1655
Fax: 312-899-4739
Email: hotline@eatright.org
Internet: http://www.eatright.org
American Heart Association
7272 Greenville Avenue
Dallas, TX 75231-4596
Tel: 800-AHA-USA1 (800-242-8721) or 214-706-1220
Fax: 214-706-1341
Internet: http://www.americanheart.org
Endocrine Society
4350 East West Highway, Suite 500
Bethesda, MD 20814-4426
Tel: 301-941-0200
Fax: 301-941-0259
Email: societyservices@endo-society.org
Internet: http://www.endo-society.org
Resources 413
National Cancer Institute (NCI)
Public Inquiries Office
6116 Executive Boulevard
Room 3036A
Bethesda, MD 20892-8322
Tel: 800-4-CANCER (800-422-6237); TTY: 800-332-8615
Email: cancergovstaff@mail.nih.gov
Internet: http://www.cancer.gov
National Center on Sleep Disorders Research
National Heart, Lung, and Blood Institute
6705 Rockledge Drive
Suite 6022
Bethesda, MD 20892-7993
Tel: 301-435-0199
Fax: 301-480-3451
Email: ncsdr@nih.gov
Internet: http://www.nhlbi.nih.gov/sleep
National Heart, Lung, and Blood Institute (NHLBI) Information Center
Education Programs Information Center
P.O. Box 30105
Bethesda, MD 20824-0105
Tel: 301-592-8573; TTY: 240-629-3255
Fax: 240-629-3246
Email: nhlbiinfo@nhlbi.nih.gov
Internet: http://www.nhlbi.nih.gov
National Institute on Aging (NIA)
Information Center
P.O. Box 8057
Gaithersburg, MD 20898
Tel: 800-222-2225; TTY: 800-222-4225
Email: niaic@jbs1.com
Internet: http://www.nia.nih.gov
North American Society for Pediatric Gastroenterology, Hepatology,
and Nutrition (NASPGHAN)
P.O. Box 6
Flourtown, PA 19031
Tel: 215-233-0808
Fax: 215-233-3918
Email: naspghan@naspghan.org
Internet: http://www.naspghan.org
1 Nutrition and the Metabolic
Syndrome: A Twenty-First-Century
Epidemic of Obesity and
Eating Disorders
Christos S. Mantzoros
Lack of sufficient nutrition is the main problem of billions of persons in the under-
developed world, while excessive caloric intake leading to obesity is becoming more
and more prevalent in Western societies of affluence. As a result, obesity, which leads
to the metabolic syndrome and is thus closely associated with significant morbidity
and mortality from diabetes, cardiovascular diseases, and cancers, to mention a few, is
considered the epidemic of our century in Western societies.
Positive energy balance, as reflected by increasing BMI, is not a recent phenomenon.
BMI has been increasing for many decades, but until the mid or late 1970s, it was rather
associated with improved health and increased longevity. In the past few decades,
however, the risk-to-benefit ratio has been shifting in such a way that the continued
increase in body fatness is increasingly being recognized as underlying several chronic
disease states. This phenomenon is slowing or even reversing gains made in terms of
life expectancy in the past. More than 30% of Americans are currently overweight and
another 30% are obese, defined as a body mass index (BMI) between 25.0 and 29.9 kg m−2
and higher than 30.0 kg m−2 respectively. Moreover, if the current trends continue, it is
expected that by the year 2020 more than 50% of Americans will be obese, possibly
making obesity the “norm” and leanness the “exception.” In children, use of the term
overweight is usually preferred, to avoid potential stigmatization, and thus the definition
of obesity in children is based on exceeding the 95th percentile of BMI-for-age using
the 2000 Centers for Disease Control charts.
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_1,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
3
4 Mantzoros
Obesity is currently considered as being responsible for increasing morbidity as well
as mortality, i.e., for the deaths of several hundreds of thousands of persons every year
in Western societies. This fact makes obesity the second important potentially prevent-
able cause of death after smoking. In addition to leading to illness, obesity can reduce
significantly functional capacity and can increase disability. Realization of the above
has prompted a heightened research interest in the factors influencing energy balance,
and intensified research efforts on the links between obesity and its complications. It has
also created an increasing demand for the study of new methods to diagnose, prevent,
or treat obesity and associated comorbidities.
Negative energy balance, either due to lack of availability of appropriate nutrition
leading to starvation in underdeveloped nations, or due to voluntary (dieting for weight
loss) or involuntary caloric restriction (anorexia nervosa, exercise-induced or hypotha-
lamic amenorrhea) in developed nations, is also of increasing prevalence. Immune
dysfunction as well as certain well-defined neuroendocrine abnormalities leading to
important adverse health consequences such as osteoporosis and infertility are the end
result of energy deprivation. Research efforts to identify missing links between energy
deficiency and these pathophysiological abnormalities have also been intensified over
the past several years. In the area of epidemiology of obesity, the good news is that
increasing rates of obesity appear to be reaching a plateau either because public health
campaigns and interventions have started working and/or because almost all people with
the genetic potential to develop obesity upon exposure to adverse environmental and
dietary factors have already developed obesity. The bad news is that the prevalence of
obesity continues to rise around the world and that this rising prevalence of obesity is
associated with increasing rates of disability, morbidity, and mortality.
1. CAN WE DISCERN HOPEFUL SIGNS IN THE MIDDLE
OF THE CURRENT DIFFICULTIES CREATED BY THESE
DISEASE STATES?
Several discoveries over the past 10 years have created opportunities for prevention
and/or treatment, including discoveries of new genes, molecules, and regulatory path-
ways. Central, in my opinion, may prove to be developments in the field encompassed
by the question: How does negative energy balance lead to neuroendocrine abnormali-
ties? Recent work, mainly from our laboratory, has demonstrated that levels of an adi-
pocyte-secreted hormone, circulating levels of which reflect the amount of energy stored
in fat, i.e. leptin, fall in response to negative energy balance and this fall can lead to the
neuroendocrine dysfunction that has traditionally been associated with energy, and thus
leptin, deficiency states, such as anorexia nervosa and exercise-induced or hypothalamic
amenorrhea. Importantly, exogenous administration of leptin, in replacement doses, can
correct these neuroendocrine abnormalities in these leptin deficiency states. These novel
advances, discussed in the relevant chapters of this book, open new and exciting avenues
for diagnosing and treating these conditions in the future. Whether additional factors
may also play a role or modify the effects of leptin administration remains to be seen.
It also remains to be seen whether falling leptin levels in response to caloric/energy
deprivation in obese persons who diet to lose weight may also be responsible for their
neuroendocrine changes, which, in turn, tend to defend the original body weight and to
make the obese person regain any weight lost in response to dieting.
Chapter 1 / Nutrition and the Metabolic Syndrome 5
2. EPIDEMIOLOGY TRENDS IN CHILDREN AND ADULTS
The prevalence of obesity has been increasing steadily over the past several years.
This has been documented in both genders and in every ethnic group and socioeco-
nomic status in Western societies of affluence. Importantly, the increasing prevalence
of obesity is not confined to adults; children and adolescents are becoming increasingly
overweight and obese. This phenomenon has resulted in increasing prevalence of type
2 diabetes among adolescents and is expected to shift the age of diagnosis of obesity-
associated comorbidities, including cardiovascular diseases and cancers, earlier in life.
The potential financial, psychological, and public health implications of these changes
are enormous, and have not yet been fully appreciated.
Recent evidence indicates that in addition to long-recognized genetic and environmen-
tal factors, including nutrition and exercise, social networks are closely associated with
and may play an important role in the spread of obesity. What are the links between sig-
nificant interpersonal relationships, human behavior, and the pathogenesis of obesity and
its complications? What is their impact on obesity prevention and treatment in societies
of affluence, as well as in developing societies? Also, how does inappropriate nutrition
lead to obesity and how is obesity linked to morbidity and mortality? A considerable
amount of work is currently underway to identify and characterize the environmental,
social, genetic, cognitive, sensory, metabolic, hormonal, and neural factors leading to
obesity and associated comorbidities. The end result is the significant growth of specific
clusters of knowledge in each one of the above specific scientific areas; over the past
15 years, none is currently emerging, unfortunately, as developed enough to explain a
meaningful proportion of the problem and/or to allow meaningful predictions of future
developments in the areas of prevention or treatment (see below). This not only underlines
the multifactorial pathogenesis of the problem but is also considered by many as the last
step before major breakthroughs occur on the basis of this accumulating knowledge.
Significant progress is being made in the scientific area of hormonal and other factors
linking excessive amounts of energy stored in adipose tissue with insulin resistance, the
metabolic syndrome, and related complications. All these are outlined in detail in the
respective chapters of this book.
3. ENVIRONMENTAL AND EXOGENOUS INFLUENCES
AS OPPORTUNITIES FOR PUBLIC HEALTH INTERVENTIONS
Our current environment is distinctly different from the one our ancestors encoun-
tered several centuries or even just a century ago. One would thus argue that obesity may
be, in part, the result of several factors set in motion by changes in the environment we
live in, including the immediate availability of food at the expense of a lower cost and
less physical labor, less physical activity, and possibly potential hormonal and epige-
netic effects. Questions related to these notions are not only what the best interventions,
including diet and exercise, should be, but also how could one help people adhere to an
appropriate intervention program for the long term?
Two commonly attacked environmental factors are food marketing practices and in-
stitutionally and technologically driven reductions in physical activity. Yet, many have
argued that, despite emerging data from controlled interventional studies, available data
supporting the above are largely circumstantial and observational in nature. We all realize,
however, that if we are to make pervasive and enduring changes to the prevalence of
6 Mantzoros
obesity and associated comorbidities, it is likely that we will need to make pervasive
and enduring changes to the ways we live across our entire lifespan and these changes
are admittedly difficult to implement.
4. MECHANISMS UNDERLYING THE LINK BETWEEN NUTRITION,
METABOLISM, AND DISEASE STATES AS OPPORTUNITIES
FOR MEDICAL INTERVENTIONS
Although we realize that obesity is associated with adverse health outcomes, we do
not fully understand the mechanisms underlying these associations. New genes linked
to obesity have been discovered and novel neuroendocrine mechanisms have been pro-
posed. Although scientific developments in basic and translational research over the
past decade have greatly advanced our understanding of the mechanisms underlying the
development of the metabolic syndrome and associated abnormalities, as discussed in
detail herein, much more needs to be done in the not so distant future.
5. HOW EFFECTIVE ARE WE IN ACHIEVING OUR GOALS?
Assuming that weight loss is desirable, can we really achieve it? Behavioral modifi-
cations such as diet and exercise, while first-line recommendations, remain ultimately
largely ineffective at maintaining long-term weight loss at desirable levels. Despite
intensive research efforts in the field, it remains to be fully elucidated which diet or die-
tary pattern, if any, is the most beneficial in terms of reducing weight loss or improving
metabolic profile. This is related, in part, to the difficulty in reproducing in an experi-
mental setting the real life dietary patterns of populations, let alone to perform long-
term clinical trials utilizing these specific diets or dietary patterns. Thus, although data
from interventional studies have started to emerge, current dietary recommendations are
based mainly on expert opinion, based, to a large extent, on observational studies (which
do not prove causality), expected outcomes and risk–benefit estimations.
We discuss herein the effects of different treatment modalities, including behavioral
modifications such as diet and exercise, pharmacotherapy, and bariatric surgery, on
obesity and its comorbidities, including cardiovascular risk factors, risk for malignancy,
bone disease, biliary disease, and overall quality of life. Pertinent randomized controlled
clinical trial and meta-analysis data are discussed and when these are not available, or
do not fully elucidate relevant questions, data from observational studies and case series
are reported in the relevant chapters of this book.
6. WHERE WOULD WE LIKE TO BE IN THE NOT
SO DISTANT FUTURE?
In energy deficiency states we clearly need to advance further our understanding of
the role of leptin (and other hormones) to improve and/or correct the neuroendocrine
abnormalities of women with hypothalamic amenorrhea and anorexia nervosa as well
as those of obese subjects dieting to lose weight and/or having had surgery for obes-
ity. We also need conclusive evidence from randomized trials on whether leptin and/or
other treatment options could also improve the osteoporosis of subjects with anorexia
nervosa or hypothalamic amenorrhea. Importantly, we need to learn whether the effect
Chapter 1 / Nutrition and the Metabolic Syndrome 7
of leptin in improving neuroendocrine function could facilitate weight maintenance of
obese subjects who strive to lose weight. Much needed investigations are underway in
this area.
With obesity affecting greater numbers of people each year and with currently avail-
able methods having only modest success to reduce the increasing prevalence of obesity,
there is an urgent need to develop better weight loss and weight maintenance programs.
We also need to clearly identify the many genetic and environmental components that
are involved in the pathogenesis of the problem and to carefully study the underlying
molecular, cellular, and hormonal mechanisms. On the basis of elucidating these factors,
effective diagnostic tools and pharmaceuticals could hopefully be designed, appropriate
behavioral modification programs could be investigated, and well-informed public health
recommendations could be formulated to direct and implement pervasive, effective, and
enduring changes to the ways we live our lives.
7. WHAT CAN WE RECOMMEND TODAY?
Diet and exercise are the cornerstones of prevention and treatment of obesity and
related disorders. Although dietary recommendations have been changing over the past
few years, it is hoped that, as we learn more from both observational and interventional
studies, our recommendations will continue to be refined and will hopefully prove to
be more and more effective. It is also hoped that diagnostic and therapeutic methods
will continue to improve significantly. New medications and new surgical methods are
continually tested, developed, and applied. We present herein our current understand-
ing of underlying scientific principles and current recommendations with the explicit
understanding that medical approaches should not only be characterized by continuous
quality improvements but need to also be individualized and guided by the responsible
treating physician.
Each chapter in this book provides an authoritative review of the current status of
research and knowledge in each one of the most important clusters of current work in
the Nutrition and Metabolism field. Text and graphs of several chapters appeared in their
original form in the textbook “Nutrition and Metabolism”, C. Mantzoros (editor), published
by the Aristides Daskalopoulos Foundation in Athens, Greece, 2007. Material from these
chapters is reproduced herein with permission granted by the Aristides Daskalopoulos
Foundation. The chapters in this book are relatively brief, analytical, based on scientific
evidence, and are written in an accessible style. We all hope that putting together cutting-
edge research and reviewing critically current knowledge in all these fields will result in a
sum that will be greater than its individual components. We also hope that ongoing work
will lead, in the not so distant future, to a better understanding of the problems we are
facing and to a more efficient creation of novel solutions that would allow us to effectively
combat and hopefully eliminate this epidemic of the twenty-first century.
2 Genes and Gene–Environment
Interactions in the Pathogenesis
of Obesity and the Metabolic
Syndrome
Despina Sanoudou, Elizabeth Vafiadaki,
and Christos S. Mantzoros
KEY POINTS
• In recent years, the prevalence of obesity has risen sharply, becoming a major public health
problem, especially in western countries.
• According to the World Health Organization (http://www.who.int), an estimated 1 billion
adults are overweight (body mass index > 25 kg/m2), and 300 million of these are considered
clinically obese (body mass index > 30 kg/m2).
• In part as a result of the rising prevalence of obesity, the incidence of the metabolic syndrome
and type 2 diabetes are also reaching the levels of an epidemic.
• Although our genetic make-up has not changed significantly over the last 50 years, our diet
and lifestyle have. This has unveiled how genetic predisposition can affect our response to
environmental factors such as nutrition and exercise.
• In the present chapter we discuss how our genes, alone and in combination with the environ-
ment, can give rise to obesity, the metabolic syndrome and diabetes.
Key Words: Mutations, Polymorphisms, Chromosomal loci, Animal models
1. OBESITY
Obesity is a complex trait with multifactorial etiology, including environmental,
behavioral, and genetic factors. The genetic contribution to human body weight has been
established through family studies, investigations of parent–offspring relationships, and
the study of twins and adopted children (1,2). The estimated heritability for body weight
is 40–70% (3). Although obesity was first considered to be a disease that obeys Mendelian
inheritance, the application of continuously evolving molecular biology technologies
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_2,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
11
12 Sanoudou, Vafiadaki, and Mantzoros
has revealed a far more complex picture for this metabolic disease and has led to fascinating
new developments.
The contribution of genetic factors to obesity can be either a single, dysfunctional
gene (monogenic obesity) or, as in the case of common (polygenic) obesity, numerous
genes that make up minor contributions in determining the phenotype.
In general, the two methods used for the study of genetic factors in complex diseases
include the candidate gene approach and the genome-wide scan approach. The candidate
gene approach examines the association of a given allele and the presence of the disease,
while the genome-wide scan, or linkage analysis, locates genes through their genomic
position and is based on the rationale that family members sharing a specific phenotype
will also share chromosomal regions surrounding the gene involved. Linkage and linkage
disequilibrium analysis in specific rely on the fact that genes with similar chromosome
positions will only rarely be separated during genetic recombination, so susceptibility
to causative genes can be localized by searching for genetic markers that cosegregate.
In addition to genetic studies in human families, the existence of naturally or genetically
modified animal models has provided valuable information on our understanding of the
pathophysiology of disease. The mouse represents the most frequently used species for
the creation of transgenic or gene knockout animals, allowing the analysis of the effects
of gene overexpression, modification, or deletion. Rats are also used for transgenic stud-
ies, but this animal model has practical and technical disadvantages over the mouse model
and hence is less frequently used. Transgenic animal models provide critical tools for
in vivo functional characterization of single genes and for the search of unknown genes
implicated in disease manifestation. Nevertheless, there are also limitations that call for
great care in interpreting results from transgenic animal models and in translating them
to humans. For example, loss or overexpression of individual proteins may produce
compensatory mechanisms that could mask the resulting phenotype. Most important
however, the phenotypic or pathophysiological consequences of genetic manipulation
in animal models may not always match the human disease (4).
1.1. Monogenic Obesity
Initial knowledge on the genetic involvement in monogenic obesity was derived from
large-scale linkage analysis in obese mice carrying naturally occurring mutations. These
analyses have pointed to disease-related loci and have identified the majority of gene
mutations leading to monogenic obesity in mice (3). In particular, the genetic charac-
terization of naturally occurring obese animal models, such as ob/ob, db/db, fat and
tubby mice, led to the discovery of recessive mutations in the genes encoding leptin
(Lep or ob), leptin receptor (Lepr or db), carboxypeptidase E (Cpe, or fat), and tubby
(Tub) (5,6). Furthermore, the latest murine obesity gene map identified 248 genes that,
when mutated or expressed as transgenes in the mouse, result in phenotypes affecting
body weight and adiposity (7). Transfer of this knowledge to clinical cases has con-
firmed the role of the above genes in human monogenic obesity and uncovered the
critical role of the leptin/melanocortin pathway in the regulation of energy homeostasis
(8). Briefly, this hypothalamic pathway is activated following the systemic release of
leptin and its subsequent interaction with the leptin receptor located on the surface of
Chapter 2 / Genes and Gene–Environment Interactions 13
neurons of the arcuate nucleus of the hypothalamus. The downstream signals that regu-
late energy homeostasis are then propagated via proopiomelanocorin (POMC), cocaine-
and amphitamine-related transcript (CART) and the melanocortin system (9,10). While
POMC/CART neurons synthesize the anorectic peptide α-melanocyte-stimulating hor-
mone (α-MSH), a separate group of neurons express the orexigenic neuropeptide Y
(NPY) and the agouti-related protein, which acts as a potent inhibitor of melanocortin 3
receptor (MC3R) and melanocortin 4 receptor (MC4R).
To date, mutations in 11 different genes (Table 1), including LEP, LEPR, POMC,
and proconvertase 1 (PC1), have been linked to obesity, in nearly 200 patients (7,30).
Patients with monogenic obesity have extremely severe phenotypes that present in
childhood and are often associated with additional behavioral, developmental, and
endocrine disorders (31). MC4R-linked obesity represents the most prevalent form of
Table 1
Genes Implicated in Monogenic Obesity
Mode of
Gene transmis-
Gene symbol Locus sion Obesity Reference
Leptin LEP 7q31.3Recessive Severe, from first 11–13
days of life
Leptin receptor LEPR 1q31 Recessive Severe, from first 14, 15
days of life
Proopiomelano- POMC 2p23.3 Recessive Severe, from first 16, 17
cortin month of life
Proconvertase 1 PC1 5q15–q21 Recessive Considerable, from 18
first month of life
Melanocortin-4- MC4R 18q22 Dominant Variable severity, 19–22
receptor early onset
Single-minded SIM1 6q16.3–q21 Dominant Severe, from 23
homolog 1 childhood
Neurotropic NTRK2 9q22.1 Dominant Severe, from first 24
tyrosine kinase months of life
receptor type 2
Corticotropin-re- CRHR1 17q12–q22 Dominant Severe, early onset 25
leasing hor-
mone receptor 1
Corticotropin-re- CRHR2 7p14.3 Not known Not known 25
leasing hor-
mone receptor 2
G-protein-coupled GPR24 22q13.3 Dominant Severe, early onset 26
receptor 24
Melanocortin-3- MC3R 20q13.2 Dominant Severe, early onset 27–29
receptor
14 Sanoudou, Vafiadaki, and Mantzoros
monogenic obesity identified to date, representing ~2–3% of childhood and adult obesity
(30,32,33). MC4R is a G-protein-coupled receptor with seven transmembrane domains
that plays an important role in controlling weight homeostasis (10). MC4R knockout
mice develop morbid obesity and increased linear growth, whereas heterozygous mice
are also obese but with a varying degree of severity (34). Investigations in the molecular
mechanisms by which loss of function mutations in MC4R cause obesity have suggested
a number of functional anomalies, including abnormal MC4R membrane expression,
a defect in agonist response, and disruption in the intracellular transport of the protein
(35). Other single gene mutations leading to obesity involve single-minded homolog
1 (SIM1), melanocortin receptor 3 (MC3R), and neurotrophic tyrosine kinase receptor
type 2 (TRKB/NTRK2) (23,24,27).
The major goal of the extensive ongoing research is the development of therapies
targeting monogenic obesity, in order to ameliorate the metabolic status of obese in-
dividuals. Leptin therapy, by subcutaneous injection of leptin in children and adults
deficient in this adipokine, markedly reduced their body weight, having a major effect
on reducing food intake and on other dysfunctions, including immunity (36). Although
treatments are not available yet for cases of LEPR, POMC-, PC1-, SIM1-, MC4R-, and
TRKB-linked obesity, preliminary studies suggest that targeted therapies could be pos-
sible to develop (37).
1.2. Syndromic Obesity
In addition to the monogenic forms of obesity, this phenotype is also associated with
many genetic syndromes. Syndromic obesity was initially thought of as monogenic;
however, the contribution of multiple genetic factors in a syndrome is significantly more
challenging than localizing the single gene involved in monogenic disorders.
There are currently 20–30 Mendelian disorders in which, in addition to mental retar-
dation, dysmorphic features, and organ-specific developmental abnormalities, patients
are also clinically obese (30,31). Such cases are referred to as syndromic obesity. These
syndromes arise from discrete genetic defects or chromosomal abnormalities and can be
either autosomal or X-linked disorders. The most common disorders known are Prader–
Willi syndrome (PWS), Bardet-Biedl syndrome (BBS), and Alström syndrome (38).
PWS, the most frequent of these syndromes (1 in 25,000 births), is characterized by
obesity, hyperphagia, diminished fetal activity, mental retardation, and hypogonadism.
PWS is caused by the absence of the paternal segment 15q11.2–q12, through chromo-
somal loss (39–41). Several candidate genes in this chromosomal region have been
studied; however, the genetic basis of polyphagia remains undefined because none of
the PWS mouse models have an obese phenotype (42). One genetic candidate that may
disrupt the control of food intake is the gastric hormone ghrelin, which could act through
the regulation of hunger and stimulation of growth hormone (43).
BBS is characterized by early onset obesity, retinal dystrophy, morphological finger
abnormalities, mental disabilities, and kidney diseases (44,45). To date, BBS has been
associated with at least 12 distinct chromosomal locations, with several mutations
identified so far (46–57). Although the precise function of the BBS proteins is yet to
be determined, current data support a role in cilia function and intraflagellar transport
(58–60).
Chapter 2 / Genes and Gene–Environment Interactions 15
Alström syndrome is a very rare disorder, which in addition to obesity, is associated with
congenital retinal cone dystrophy, cardiomyopathy, and type 2 diabetes (61,62). Family
studies have identified several mutations in the Alström syndrome 1 gene (ALMS1), the
majority of which are nonsense and frameshift (insertion or deletion) mutations predicted
to lead to premature protein termination (63–65). ALMS1 is a ubiquitously expressed
protein with recently proposed functional involvement in cilia formation (66,67).
As the above genetic syndromes involving obesity are rare, their underlying genetic
involvement has been difficult to decipher. Furthermore, even in the cases where the
responsible genes have been identified, the pathophysiological link between the protein
products and the development of the disease has not yet been fully elucidated.
1.3. Polygenic Obesity
Polygenic, or common, obesity arises when an individual’s genetic makeup is sus-
ceptible to an environment that promotes energy intake over energy expenditure. Spe-
cifically, environments in most westernized societies favor weight gain rather than loss
because of food abundance and lack of physical activity, thus rendering common obesity
as a major epidemic currently challenging the medical and financial resources in these
societies (37).
A range of polygenic mouse models have been generated through inbreeding of
mouse lines or repeated selections of noninbred mice, and have enabled the identifica-
tion of >408 quantitative trait loci (QTL) associated with obesity (http://obesitygene.
pbrc.edu). A recent meta-analysis of ~280 QTL, from 34 mouse cross-breeding experi-
ments involving >14,500 mice, revealed 58 QTL regions associated with body weight
and adiposity (http://www.obesitygenes.org) (68). Different QTL have been associated
with the age of onset and gender in obesity, while certain loci may only contribute to
obesity by interacting with other loci (69).
In humans, studies of polygenic obesity are based on the analysis of single nucle-
otide polymorphisms (SNPs) or repetition of bases (polyCAs or microsatellites) lo-
cated within or near a candidate gene. These studies are carried out in family members
(family study) or unrelated individuals (case–control study), and their objective is to
determine a potential association between a gene’s allelic variant and obesity-related
traits (70). However, unlike monogenic obesity, many genes and chromosomal regions
contribute to the common obese phenotype (7,71). For this purpose, large DNA banks
have been established from different populations throughout the world and are used for
the extensive investigation of large number of genes and chromosomal regions. The
findings of these genetic studies are reported every year by the Human Obesity Gene
Map consortium. According to their latest report, 253 QTL have been identified, in 61
genome-wide scans (7). All chromosomes, except the Y chromosome, have been found
linked with an obesity-related phenotype, such as fat mass, distribution of adipose tissue,
resting energy expenditure, or levels of circulating leptin and insulin. Genes associated
with obesity include solute carrier family 6 (neurotransmitter transporter) member 14
(SLC6A14), glutamate decarboxylase 2 (GAD2), and ectonucleotide pyrophosphatase/
phosphodiesterase I (ENPPI) (72–74). These genes have been implicated in a variety of
biological functions such as the regulation of food intake, energy expenditure, lipid and
glucose metabolism, adipose tissue development, and inflammatory processes. Recent
16 Sanoudou, Vafiadaki, and Mantzoros
genome-wide association studies have identified genetic variants (SNPs) associated with
obesity-related traits in both children and adults, in the fat mass and obesity associated
(FTO) gene (75–77, 272). It has been proposed that through its catalytic activity, FTO
may regulate the transcription of genes involved in metabolism (78).
In contrast to genetically identical mice, whose environments can be controlled, the
genetic and environmental diversity in humans has proved problematic for data replica-
tion. To date, only 22 obesity-related genes are supported by at least five positive studies
(7,37). The reasons for the lack of replication in association and linkage studies include
lack of statistical power to detect modest effect, lack of control over type I error rate, and
overinterpretation of marginal data (79). Thus, the use of novel approaches may provide
the means to circumvent classical statistical obstacles in identifying new candidate genes
and possible gene–environment interactions (see Sect. 4).
The immense ongoing research on the identification of new molecular targets for an-
tiobesity drugs and the significance of the generated findings is reflected by the rapidly
increasing number of patent applications. Specifically, a total of 173 US patents were
issued between January 2001 and March 2004, with the word “obesity” included in the
abstract (80,81). Among the molecular targets with the highest number of new patents
are the serotonin receptor ligands (24 patents), neuropeptide Y receptor ligands (20
patents), and adrenergic receptor ligands (20 patents).
2. THE METABOLIC SYNDROME AND TYPE 2 DIABETES
2.1. The Metabolic Syndrome
The term metabolic syndrome (occasionally called insulin resistance syndrome) refers
to a constellation of clinical findings including obesity, hypertension, hyperlipidemia,
and insulin resistance, with increased risk for type 2 diabetes and cardiovascular disease.
It has also been linked with chronic kidney disease, liver disease with steatosis, fibrosis,
and cirrhosis, and cognitive decline and dementia. Despite recent controversy regarding
the concept of a metabolic syndrome, the International Diabetes Federation (IDF) devel-
oped a new unifying worldwide definition building upon the World Health Organization
(WHO) and ATP III definitions, as will be discussed in later chapters (82).
On the basis of the IDF definition, almost 40% of US adults are classified as having
the metabolic syndrome (83). Although environmental factors such as smoking, low
economic status, high intake of carbohydrates, no alcohol consumption, and physical
inactivity can play a role in the development of the metabolic syndrome, a series of evi-
dence indicates that there is also a genetic component involved. Specifically the metabolic
syndrome has different prevalence between men and women, and among ethnic groups,
as well as different concordance rates between monozygotic twins. Furthermore, there
is increased incidence in individuals with a parental history of metabolic syndrome, and
a general familial clustering of the metabolic syndrome and its components (83–91).
Ongoing work on spontaneous and engineered animal models has revealed that several
genetic loci are associated with metabolic syndrome components in different rodent
models (92). Examples of metabolic syndrome rodent models include the spontaneous
hypertensive rat (SHR), the transgenic SHR overexpressing a dominant-positive form of
the human sterol regulatory element binding transcription factor 1 (SREBP-1), the SHR/
Chapter 2 / Genes and Gene–Environment Interactions 17
NDmcr-cp rat, the polydactylous rat strain (PD/cub), the obese Zucker rats (OZR), the
New Zealand obese (NZO), the Wistar Ottawa Karlsburg W rats, as well as congenic,
consomic, and double-introgressed strains (93–100).
Linkage analyses in patients with the metabolic syndrome have aimed at identify-
ing loci with pleiotropic effects on multiple aspects of the syndrome. Several different
linkage analysis approaches have been applied in the study of the metabolic syndrome,
such as principal components or principal factor analysis, multivariate analysis, meta-
bolic syndrome score from combined residuals and the structural equation model (101).
One of the most consistent findings was the linkage to chromosome 1q, while multiple
phenotypes linked to this region indicate that it likely harbors a gene with pleiotropic
effects on measure of glucose, lipids, hypertension, and adipocity, or multiple genes that
contribute to each one of these features (102–106). Other consistent loci implicated in
the development of the metabolic syndrome include chromosomes 2p, 2q, 3p, 6q, 7q,
9q, and 15q (103,106–111).
Many of these loci have also been linked to individual components of the metabolic
syndrome. For example, chromosome 2p has been linked to serum triglycerides, systolic
blood pressure, obesity, body fat percentage, and HDL (111–113), while chromosome
7q has been linked to systolic blood pressure, triglyceride–HDL-C ratio, fasting glucose,
insulin, and insulin resistance (114–116).
Despite the wide use and important findings that have emerged from linkage analysis,
this method presents with a number of limitations that need to be carefully considered
and addressed in the interpretation of current findings and the design of future studies.
Some of the common obstacles in this type of studies are the inadequate statistical power,
the multiple hypothesis testing, the population stratification, the publication bias and
phenotypic variation (117). The identification of true genetic associations in common
multifactorial conditions, such as the metabolic syndrome, requires large studies con-
sisting of thousands of subjects. This need is further accentuated by the large number of
implicated genetic loci and their potentially small contribution to the phenotype when
individually considered.
In parallel to linkage and association studies, several studies have evaluated the
contribution of specific candidate genes to the metabolic syndrome pathogenesis.
These candidate genes have been selected based on their biological function and/or
previous associations to any of the phenotypic aspects of the syndrome. However, the
large number of metabolic pathways implicated in the pathogenesis of the metabolic
syndrome (including insulin signaling, glucose homeostasis, lipoprotein metabolism,
adipogenesis, inflammation, coagulation, etc.) renders this search a highly challenging
task that has yielded a relatively limited success. There are many examples of genes
directly or indirectly implicated in the development of the metabolic syndrome or spe-
cific clinical features related to it, but an equal number of negative studies have also
been published (118).
The peroxisome proliferator-activated receptor γ (PPARg) is one of the strong can-
didates for conferring susceptibility to the metabolic syndrome because of its involve-
ment in adipocyte differentiation, fatty acid metabolism, insulin sensitivity, and glucose
homeostasis (119–121). Despite some inconsistencies in the PPARγ association studies,
the overall evidence seems to suggest that PPARg polymorphisms can increase the risk
for developing the metabolic syndrome (122–124). Direct correlations to the metabolic
18 Sanoudou, Vafiadaki, and Mantzoros
syndrome have also been described for genetic variants of the β3-adrenergic receptor
(ADRb-3), nitric oxide synthase 3 (NOS3), angiotensin I converting enzyme (ACE),
beacon (BEACON), lamin A/C (LMNA), interleukin-6 (IL-6), interleukin-β (IL1-b), and
protein tyrosine phosphatase nonreceptor type 1 (PTPN1) genes (122,125–131). Inter-
estingly, PPARg and IL1-b polymorphisms have been implicated in gene–environment
interactions (see Sect. 4).
Fatty acid binding protein 2 (FABP2) and apolipoprotein C-III (APOC3) polymor-
phisms have been directly associated with increased risk for dyslipidemia and the
metabolic syndrome in Asian-Indians (132). Other examples include a number of lipid-
sensitive transcription factors (nuclear receptor subfamily 1, member 4 (FXR), nuclear
receptor subfamily 1, member 3 (LXR-a), retinoid X receptor α (RXR-a), PPAR-a,
PPAR-d, peroxisome proliferator-activated receptor (PGC1-a), PCG1-b, sterol regu-
latory element binding transcription factor 1 (SREBP-1c)) that have been implicated
in the development of dyslipidemia, one of the very early features of the metabolic
syndrome (124). Since lipoprotein metabolism plays a central role in the metabolic
syndrome, several genes related to the former are also good candidates for the latter.
These include variants of scavenger receptor class B, member 1 (SCARB1), ATP-binding
cassette subfamily A, member 1 (ABCA1), cholesteryl ester transfer protein (CETP),
lipoprotein lipase (LPL), lipase (LIPG), pancreatic lipase (PNLIP), apolipoprotein A-V
(APOA5), and the apolipoprotein gene clusters ApoA1/C3/A4/A5 and ApoE/C1/C2 that
affect HDL-cholesterol and triaglyceride metabolism (133–138).
2.2. Hypertension
Hypertension is one of the components of the metabolic syndrome and a major risk
factor for cardiovascular disease. Similar to obesity and the metabolic syndrome, hyper-
tension seems to be the outcome of combined genetic and environmental etiologies (139).
Mutations in eight genes have been identified to cause severe but rare forms of monogenic
hypertension (140). Interestingly, all of these genes participate in the same physiological
pathway in the kidney, altering net renal salt reabsorption. However, the genetic factors
behind the common, less severe forms of hypertension, collectively termed essential
hypertension (i.e., hypertension with unknown cause), are poorly understood. A large
number of candidate gene, linkage, and association studies have sporadically impli-
cated a range of different genetic loci in hypertension development. Polymorphisms
in the angiotensinogen (AGT), the natriuretic peptide receptor A (NRP1), and ACE are
prime examples of the most consistent findings in the literature (141–144). Nonetheless,
genome-wide linkage analyses have not consistently implicated specific chromosomal
loci, suggesting a model in which there may be many loci, each imparting small effects
on hypertension in the general population (145–148). Similar to other multifactorial
diseases, the study of hypertension in humans will require the consistent replication of
results in large and rigorously characterized populations that are well suited for detect-
ing alleles imparting small effects. Such populations would include cohorts of unrelated
individuals as well as family-based linkage disequilibrium studies. These latter tests
minimize the chance of false-positive associations arising from population admixture
of individuals of different genetic backgrounds (149). Meta-analysis of the combined
results from multiple different studies/populations can also greatly contribute towards
Chapter 2 / Genes and Gene–Environment Interactions 19
this end, as for example in the case of a methylenetetrahydrofolate reductase (MTHFR)
polymorphism that appears to be significantly associated with hypertension in multiple
populations (150).
In parallel to human studies, a series of spontaneous and engineered animal models
of hypertension have been extensively studied. For example, inbred rat strains that
display hypertension as an inherited trait have long been used as a means for iden-
tifying genes that can give rise to essential hypertension. Examples of these strains
include SHRs, Dahl salt-sensitive rats, Sabra hypertensive-prone rats, Molan, Lyon,
fawn-hooded and Prague hypertensive rats (151). Importantly, some of the findings
in these animal models have later been translated to humans, such as in the case of
brain and muscle Arnt-like protein-1 (Bmal1) polymorphisms which are associated
with susceptibility to hypertension and type 2 diabetes (152). Congenic and consomic
rat strains have also been used to identify QTL for hypertension, in an effort to elimi-
nate the variability arising from the often heterogeneous genetic background of these
animals (151,153–157). In support of the notion that hypertension is a polygenic
condition, at least one blood-pressure-related QTL has been identified on almost all
rat chromosomes (151). Genetically engineering mouse models with increased or
decreased expression of targeted genes has also provided useful insights (158). For
example, deletions of various genes (including the bradykinin B2 receptor, D1A and
D3 dopamine receptors, atrial natriuretic peptide, endothelial nitric oxide synthase, and
others) have resulted in elevated blood pressure, while in other cases, gene mutations
have had little or no effect (159–163). Furthermore, mouse models have enabled the
confirmation of various observations in humans, and the more detailed characteriza-
tion of the disease physiology (158).
2.3. Type 2 Diabetes
Diabetes mellitus represents a group of metabolic disorders characterized by hypergly-
cemia resulting from defects in insulin secretion, insulin action, or both. The pathogenic
processes involved in the development of diabetes range from autoimmune destruction
of the pancreatic β cells with consequent insulin deficiency to abnormalities that result
in resistance to insulin action (164). There are two main etiopathogenetic categories of
diabetes: (1) type 1 diabetes, which is caused by deficiency of insulin secretion and rises
independently of obesity or the metabolic syndrome (will be covered in Sect. 3), and
(2) type 2 diabetes, which is caused by a combination of resistance to insulin action and
inadequate compensatory insulin secretion. Type 2 diabetes, or noninsulin-dependent
diabetes mellitus, is the most frequent form of diabetes, accounting for 90% of the dis-
ease prevalence, with an estimated 150 million affected people worldwide (165,166).
Overall, type 2 diabetes is characterized by impairment of insulin secretion and decrease
in insulin sensitivity. Initial studies in families with rare monogenic forms of diabetes
pointed towards a genetic component of type 2 diabetes (167). However, it has become
evident that the incidence of the disease is also affected by environmental influences,
such as lifestyle and diet.
On the basis of the role of genetic factors, type 2 diabetes may be divided into mono-
genic and polygenic forms, where monogenic forms are the consequence of rare muta-
tions in a single gene whereas polygenic forms are the result of the interaction between
the environment and genetic contribution of many different genes (168,169).
20 Sanoudou, Vafiadaki, and Mantzoros
2.3.1. Polygenic Type 2 Diabetes
Polygenic, or the common form, type 2 diabetes is a complex and heterogeneous
disorder that is influenced by the contribution/impact of multiple genes and various
environmental factors that can affect disease predisposition. In many cases obesity and
the metabolic syndrome precede the development of type 2 diabetes. Owing to its com-
plexity, with both gene–gene and gene–environment interactions, the genetic influences
on this form of type 2 diabetes have been difficult to elucidate and the identification of
genes has not been easily achieved (Fig. 1).
Animal models for type 2 diabetes have enabled the study of the molecular pathways
involved in disease pathophysiology, providing useful information on the molecular
etiology of type 2 diabetes and pointing towards potential therapeutic interventions. The
numerous spontaneous animal models for type 2 diabetes have facilitated our understand-
ing of disease physiology and have aided towards the identification of underlying genetic
factors. Examples of such models include the Nagoya-Shibata-Yasuda (NSY) mouse
model, which spontaneously develops diabetes in an age-dependent manner, the diabetic
db/db mice and the KK mouse strain, which shows inherently glucose intolerance and
insulin resistance (170–172). Additional spontaneous animal models presenting insulin
resistance and impaired insulin secretion include the Goto Kakizaki rat, the Otsuka Long-
Evans Tokushima fatty (OLETF) rat and the Zucker Diabetic Fatty rat model (173–175).
Genome-wide linkage scans in OLETF rats have identified susceptibility loci on chro-
mosomes 1, 7, 14, and the X chromosome, while a sequence variation in the hepatocyte
nuclear factor 1β (Hnf1b), a gene implicated in human MODY (maturity-onset diabetes
of the young) disease, was identified in the NSY mouse model (176–178).
In addition to spontaneous animal models, an increasing number of genetically en-
gineered models have been generated for type 2 diabetes. In an attempt to recreate the
human disease in animals, investigations have focused on the understanding of β-cell
dysfunction or insulin resistance pathways. Depending on the targeted protein and its
importance on insulin signaling, various degrees of insulin resistance can be created.
Insulin-receptor (IRS)-deficient mice were among the first knockout mice to be generated
with affected proteins in the insulin signaling cascade. Heterozygous mice exhibit normal
glucose tolerance and only 10% of adult animals develop diabetes, while homozygous
Fig. 1. Progress in the identification of susceptibility genes for type 1 and type 2 diabetes over
the past decade.
Chapter 2 / Genes and Gene–Environment Interactions 21
IRS-deficient mice rapidly develop diabetes and die within 3–7 days after birth, thus
demonstrating the essential role of IRS in the control of glucose metabolism (179,180).
Deficiency of the insulin receptor substrate 1 protein (IRS-1) in mice results in postnatal
growth retardation with only mild insulin resistance and no diabetes, whereas deletion
of IRS-2 causes impaired insulin signaling and β-cell function, resulting in progressive
deterioration of glucose metabolism (181,182). On the other hand, IRS-3 and IRS-4
knockout mice show respectively either mild glucose intolerance or have no phenotype,
therefore suggesting that they are unlikely to play a major role in glucose homeostasis
(183,184).
In an attempt to resemble the polygenic nature of type 2 diabetes, polygenic animal
models containing combined gene disruptions have been created. Double heterozygous
mice for IRS and IRS-1 exhibit a synergistic impairment on insulin action, presenting
a phenotype that is much stronger than individual gene deficiency (185). In contrast to
their respective individual gene deficiency models, double knockout mice for IRS-1
and β-cell glucokinase (Gck) develop overt diabetes, demonstrating that combination of
minor mutations in genes involved in either insulin action alone or insulin secretion and
action can cause diabetes (186). Overall, polygenic mouse models have demonstrated
that, when combined, minor defects in insulin secretion and action can lead to diabetes,
therefore emphasizing the interaction between different genetic loci in diabetes.
Animal models with tissue-specific inactivation of insulin receptor genes have also
been generated, in order to assess insulin action in individual tissues. These include the
muscle-specific insulin receptor knockout mice, the liver insulin receptor knockout mice,
and the β-cell insulin receptor knockout mice (187–189). Such tissue-specific models
have helped in dissecting the contribution of individual insulin-responsive organs to
glucose metabolism.
In humans, candidate gene analyses towards the identification of type-2–diabetes-
related genes have focused on genes implicated in insulin resistance and particularly
in β-cell development, insulin signaling, or hypothalamic regulation. This has included
genes such as the PPARg, the ATP-binding cassette subfamily C member 8 (ABCC8) and
potassium-inward rectifier 6.2 (KCJN11), and IRS-1 (119,190). The best-characterized
and most robust variant is the highly prevalent Pro21Ala polymorphism in PPARg. Two
meta-analyses have shown that the proline allele, which is the most frequent allele, is
associated with a moderate increase in risk for type 2 diabetes. Furthermore, a 21–27%
risk reduction was shown for the presence of the alanine allele, hence suggesting that
the alanine genotype results in greater insulin sensitivity (191–193).Other meta-analyses
studies have determined that in the KCJN11 gene, which encodes the ATP-sensitive
potassium channel subunit Kir6.2, the frequent variant E23K shows association with a
slightly increased susceptibility to type 2 diabetes in some populations, with the risk for
the disease increasing by about 15% in the presence of the K allele (190,194). However,
in many cases the initial associations have not been replicated in subsequent studies.
For example, a meta-analysis of ~9,000 individuals initially determined that the G971R
variant in IRS-1 had a significant effect on diabetes risk; however, two subsequent studies
failed to confirm this association (195–197).
To date, more that 50 linkage studies have been conducted in a variety of popula-
tions. Although initially the regions of linkage determined by the different studies
were inconsistent (because of differences in study design, family configuration, ethnic
22 Sanoudou, Vafiadaki, and Mantzoros
heterogeneity), the completion of additional scans revealed that some chromosomal
regions, and in particular chromosomes 1q21–24, 1q31–q42, 9q21, 10q23, 11p15, 12q12,
19q13, and 20q11–q13, are showing positive association with the disease in more than
one study (198). Calpain 10 (CAPN10) was the first polygenic diabetes gene to be cloned
(199) and it encodes for a ubiquitously expressed cysteine protease. Although wide-
spread acceptance of CAPN10 as a type-2-diabetes-predisposing gene was not initially
achieved, recent studies have provided further evidence for the biological importance of
CAPN10 variation in susceptibility for the disease. A meta-analysis of more than 7,500
patients of diverse ethnic origin has determined a significant association for the presence
of a CAPN10 variant (SNP-44; CAPN10-g4841 T → C) and the disease (200). It has
been proposed that genetic variants of CAPN10 might affect insulin sensitivity, insulin
secretion, or the relation between the two (201–203). Other genes associated with the
common form of type 2 diabetes include transcription factor 7-like 2 gene (TCF7L2)
(204,205), FTO (77,206,273), and ectonucleotide pyrophosphatase/phosphodiesterase
1 (ENPP1), genetic variants of which impair insulin binding to its receptor in muscle
and brain, hence leading to fat deposition (207).
The shape of genetic association studies for type 2 diabetes is set to be transformed
in the next few years, with the advent of truly genome-wide association scans. The
availability of array-based platforms that will allow the performance of massive parallel
genotyping (between 250,000 and 1 million SNPs per assay), combined with the infor-
mation provided by the International HapMap Consortium, will provide powerful means
for a global view of genetic associations in type 2 diabetes (208). Indeed, through the
simultaneous analysis of thousands of genetic variants (SNPs) in large diabetes patient
cohorts, genome-wide association studies have recently identified the solute carrier fam-
ily 30 member 8 (SLC30A8), the insulin degrading enzyme (IDE), and hematopoetically
expressed homeodomain HHEX (HHEX/IDE) genes, as well as the cyclin-dependent
kinase 5 (CDK5) regulatory subunit associated protein-1-like 1 (CDKAL1) melatonin
receptor 1B (MTNR1B) (274), the insulin-like growth factor 2 mRNA binding protein
(IGF2BP2), and the cyclin-dependent kinase inhibitor 2A (CDKN2A) genes as type 2
diabetes susceptibility genes (204,206, 209, 210). However, as these loci explain a small
proportion of the observed familial cases of the disease, it is expected that additional
loci will be revealed in the near future by further systematic screens (211).
Our understanding of the molecular pathways involved in the pathogenesis of the
disease could also be enhanced by the utilization of novel technologies. For example, the
microarray technology has been used to identify differential mRNA expression patterns
in muscle tissue of type 2 diabetes patients and normal controls (212). The application
of metabolomics, which is defined as the measurement of all metabolites present within
a cell, tissue, or organism following genetic medication or physiological stimulus, will
also contribute valuable insights into the understanding of the pathophysiology of the
disease as it provides the potential of globally profiling the metabolome of an organism
(213,214). Although few studies of metabolomics have focused on diabetes, a recent
application of the technology to type 2 diabetes has identified characteristic alterations
in the plasma phospholipids profile, therefore enabling the identification of patients from
control individuals (215,216).
Chapter 2 / Genes and Gene–Environment Interactions 23
2.3.2. Monogenic Type 2 Diabetes
The monogenic form of type 2 diabetes constitutes a small group accounting for ~5%
of the disease and is characterized by high phenotypic penetrance, early disease onset,
and often a severe clinical picture (69,168,169). The most frequent monogenic type 2 dia-
betes form is the autosomal dominant MODY, a term that was first used by Tattersall and
Fajans in 1975 (217). So far, six genes responsible for MODY have been described, and
they include hepatocyte nuclear factor-4α, -1α, -1β (HNF-4a, -1a, -1b), GCK, insulin
promoter factor 1α (IPF-1a), and neurogenic differentiation 1 (NEUROD1) (218–223).
All of the MODY genes are expressed in the pancreatic β-cells, and, with the exception
of GCK, all code for transcription factors with a role in β-cell development and func-
tion (224). Moreover, these MODY genes are functionally related, forming part of an
integrated transcriptional network. However, as in 16–45% of MODY families, termed
MODY X, there have been no mutations detected in any of the known MODY genes,
it has been proposed that additional MODY genes could exist (225,226). In addition to
the established MODY genes, mutations in familial diabetes have been implicated in
two other genes, mitogen-activated protein kinase 8 interacting protein 1 (MAPK8IP1),
which codes for another β-cell transcription factor, and ABCC8, the gene that codes for
SUR1 (227,228).
Another monogenic form of type 2 diabetes, with distinct molecular involvement, is
the maternally inherited diabetes. This is a very rare form of the disease that is caused
by mutations in mitochondrial DNA, most often by mutations in the tRNA for leucine
(229). Maternally inherited diabetes is associated with deafness (maternally inherited
diabetes with deafness) or mitochondrial encephalopathy, lactic acidosis, and stroke-like
episodes syndrome (MELAS) (230,231). Mitochondrial mutations could perturb glucose
homeostasis/metabolism through impairment of the glucosensory function of the β cells
and their decreased ability for insulin production (232).
3. TYPE 1 DIABETES
Insulin-dependent diabetes mellitus (IDDM), or type 1 diabetes, is characterized by
autoimmune destruction of insulin-producing β cells in the pancreas and severe insulin
deficiency (233). Type 1 diabetes accounts for around 10% of all cases of diabetes,
occurs more frequently in people of European descent, and affects 2 million people in
Europe and North America (234). Currently, there is a 3% global increase in incidence
per year, but this is predicted to increase considerably within the next few years (235).
Type 1 diabetes is a complex trait, the etiology of which has only been partially
characterized. It is generally recognized though that the disease has both genetic (Fig.
1) and environmental influences. The advances in our understanding of the pathophysi-
ology and the genetic factors underlying type 1 diabetes have benefited immensely
from studies on spontaneous or genetically manipulated animal models of the disease.
Autoimmune diabetes in such models shares many molecular and genetic characteristics
to human type 1 diabetes. Animal models have therefore provided valuable informa-
tion that can be applied on studies of human type-1-diabetes-associated molecular and
cellular pathways. The nonobese diabetic (NOD) mouse represents the most studied
24 Sanoudou, Vafiadaki, and Mantzoros
animal model for type 1 diabetes and has been utilized for the determination of over 20
non-HLA regions (known as insulin-dependent diabetes, Idd) associated with disease
risk in this diabetic mouse strain (236). By narrowing down genetic intervals in animal
models, a small number of candidate genes have been highlighted for association test-
ing in human patients. An example of this is illustrated by the IL-2 pathway, which was
considered as a candidate for the Idd3 locus in the nonobese diabetic mouse. Following
extensive investigation, its involvement in human disease was revealed. Analysis of
its orthologue gene in humans confirmed its association in type 1 diabetes, therefore
providing an example where genes discovered in animal models can be considered as
primary candidates for investigation in humans (236). Other widely used animal models
include the BioBreeding diabetes-prone rat and the Komeda diabetes-prone rat (237). In
addition to the naturally occurring animal models, a range of transgenic animals have
been generated for a long series of different genes, including major histocompatibility
molecules (e.g., D57, HLA-DRa, HLA-DQ6), cytokines (Il2, Tnfα, Tgfβ1), autoantigens
(proinsulin, HSP60, GAD), costimulatory molecules (Cd152, Cd80), and T-cell recep-
tors (BDC2.5, 8.3) (69).
Through association studies and linkage analysis in humans, an increasing number –
19 to date – of IDDM susceptibility loci have been identified (named by the abbreviation
IDDM and a number reflecting the order with which they were reported, e.g., IDDM1,
IDDM2, etc.) (69,238,239). The human leukocyte antigen (HLA) locus on chromosome
6p21 was the first to be associated with the disease and is thought to contribute for around
50% of the familial basis of type 1 diabetes (234,240–242). It has been shown that the
HLA-DR4-DQ8 and HLA-DR3-DQ2 haplotypes are present in 90% of children with type
1 diabetes, whereas HLA-DR15-DQ6 is found in only 1% of affected children but more
than 20% in the general population, therefore suggesting that it is protective (243). The
genotype combining the two susceptibility haplotypes (DR4-DQ8/DR3-DQ2) contributes
the greatest risk for the disease. Despite extensive research, the specific details as to how
genes in this region modulate type 1 diabetes risk have still not been fully elucidated.
The insulin gene, or IDDM2 locus, on chromosome 11p15.5 was the second locus to
be identified and is the second most common factor, contributing to 10% of the genetic
susceptibility of type 1 diabetes (244). Susceptibility in the insulin gene has been pri-
marily mapped to a variable number of tandem repeats located in the promoter region of
the gene. Shorter forms of these repeats are associated with susceptibility to the diseases
whereas longer repeats are associated with protection (245).
Other genes associated with type 1 diabetes include cytotoxic T-lymphocyte antigen
4 (CTLA4), protein tyrosine phosphatase, nonreceptor type 22 (PTPN22), small ubiq-
uitin-like modifier 4 (SUMO4), and the α-chain of interleukin-2 receptor gene (IL2R)
(246–248,275,276,277). The KIAA0350 gene, encoding for a protein with predicted
sugar binding properties, was the latest one identified (249). Overall, a number of whole
genome scans using families and affected sibling pairs performed over the past decade
have provided evidence for the existence of many additional loci associated with type 1
diabetes, including but not limited to the IDDM loci (211,250–254,278).
In a coordinated effort on the analysis of existing type 1 diabetes families for the
elucidation of the genetic etiology of the disease, the type 1 Diabetes Genetics Consor-
tium (T1DGC) (http://www.t1dgc.org) has been established. The T1DGC represents a
worldwide collaboration on the study of a large collection of patients and their families
Chapter 2 / Genes and Gene–Environment Interactions 25
from around the world. The first report from this consortium was published in 2005,
and it included a combined linkage analysis of four datasets, three previously published
genome scans, and a new dataset of 254 families (252). The T1DGC analysis included
1,435 families with 1,636 affected sibling pairs from the UK, the USA, and Scandinavia,
representing one of the largest linkage studies performed so far. In addition to HLA,
this large study determined evidence for linkage to ten other chromosomal regions. In
particular chromosomes 2q31–q33, 6q21, 10p14–q11, and 16q22–24 showed genome-
wide significance, therefore indicating a strong non-HLA genetic contribution to type
1 diabetes (252).
The T1Dbase database ( http://T1DBase.org ) represents a powerful resource,
which combines and organizes data for type 1 diabetes, focusing on the molecular
genetics and biology of disease susceptibility and pathogenesis (255). This public
database allows scientists to search across different data sources/types, and thus
find new relationships among factors contributing to the complex pathogenesis of
type 1 diabetes (256).
In addition to the genetic contributions of type 1 diabetes, it is becoming evident
that additional factors, such as environmental influences, are also involved in the de-
velopment of the disease. Such factors include viruses, such as enteroviruses, rotavirus,
and rubella (257,258). Nevertheless, even though Finland has effectively eradicated
rubella through vaccination, it has one of the highest incidences of type 1 diabetes.
This therefore supports the hygiene hypothesis, which proposes that environmental
exposure to microbes early in life promotes innate immune responses that suppress
atopy and autoimmunity. To address the role of environmental factors in type 1 dia-
betes, large-scale studies are required. For this purpose, the international consortium
Environmental Determinants of Diabetes in the Young (TEDDY; http://www.niddk.nih.
gov/patient/TEDDY/TEDDY.htm) has been established so as to follow large number
of babies with high-risk HLA genotypes during early life and thus identify infectious
agents, dietary factors, or other environmental factors that could trigger autoimmunity
in susceptible populations (234).
3.1. Evidence for Genetic Overlap between Type 1 and Type 2 Diabetes
Even though, as described above, type 1 and type 2 diabetes represent two different
disease entities, the clinical and etiological distinction between them is becoming more
difficult as there is increasing evidence of a significant overlap between the two disease
states. Clinical studies have reported that even within the same family both type 1 and
type 2 diabetes may co-occur and patients with such double genetic predisposition have
intermediate phenotype (259). As an example of common genetic predisposition, a vari-
able number of tandem repeats polymorphism in the insulin gene promoter region has
been associated with both type 1 and type 2 diabetes (259).
The “accelerator hypothesis” suggests that both type 1 and type 2 diabetes are the same
disorder of insulin resistance set against different genetic background (260). According
to this hypothesis, type 1 and type 2 diabetes are one and the same entity, distinguished
only by the rate of β cell loss. Instead of overlap between the two types of diabetes, the
hypothesis envisages overlay between the two types, with one disease representing a
subset of the other.
26 Sanoudou, Vafiadaki, and Mantzoros
4. GENE–ENVIRONMENT INTERACTION
All evidence so far appears to support a shared genetic and environmental (with diet
and exercise being among the most important) contribution to disease predisposition,
including obesity, metabolic syndrome, and type 2 diabetes (Fig. 2). Nevertheless, the
relative contribution of each of these two main parameters and the extent of their interac-
tion are difficult to determine, and varies for each condition. It is noteworthy, that although
the human genome has not changed significantly over the last few decades, the preva-
lence of obesity, metabolic syndrome, and type 2 diabetes are increasing exponentially.
Although the genetic and environmental factors have long been studied independently,
an increasing effort is now placed on deciphering the gene–environment interaction.
Obesity, metabolic syndrome, and type 2 diabetes are classic examples of such gene–
environment interactions (261–263). For example, in a cohort of 287 monozygotic and
189 dizygotic young adult male twin pairs, it was shown that sedentary twins were more
likely to develop high waist circumference if they were genetically susceptible to obes-
ity than if they were not (264). The complexity, however, of these multifactorial diseases
has emphasized the need for development of more sophisticated statistical methods that
would enable more accurate assessment of the interplay between complex combinations
of multiple gene variants and environmental factors (265).
A large set of common genetic variants are currently under study in the European
programs Nutrient–Gene Interactions in Human Obesity (NUGENOB) (http://www.
nugenob.com) and Diet, Obesity and Genes (DIOGENES) (http://www.diogenes-eu.
org). Such programs comprising both academic and industrial partners, aim to study
gene–environment interactions and thus identify genetic determinants susceptible to
environmental stimuli that are capable of influencing obesity development. Within
these programs, the use of comprehensive platforms (i.e., genetics, transcriptomics,
peptidomics, and metabolomics) coupled with clinical data will have a predominant role
in elucidating the perturbed functions leading to obesity, and ultimately in developing
better targeted therapies.
In the context of the metabolic syndrome development, a study of 303 elderly twin
pairs recently showed that glucose intolerance, obesity, and low HDL-cholesterol concen-
trations are significantly higher among monozygotic twins than among dizygotic twins,
Fig. 2. Genetic polymorphisms can affect predisposition to mutlifactorial diseases, such as obesity,
on their own or in response to environmental factors, such as nutrition and exercise.
Chapter 2 / Genes and Gene–Environment Interactions 27
indicating a genetic influence on the development of these phenotypes. In contrast, the
heritability estimates for hyperinsulinemia, hypertension, and hypertriacylglycerolemia
are low, indicating a more important environmental influence on these components
of the metabolic syndrome (266). Nevertheless, gene–environment interactions are
slowly emerging for them too. For example, polymorphisms in endothelin 1 (EDN1)
are associated with increased risk for hypertension in low-fit, but not in high-fit, white
individuals (267).
Similar observations are emerging for the other multifactorial conditions described in
this chapter, and they are likely to play a key role in addressing and reversing the current
epidemic of obesity, metabolic syndrome, and type 2 diabetes.
4.1. Nutrigenomics
One of the rapidly expanding scientific fields that address the way genes and bioac-
tive food components interact is nutrigenomics. It specifically focuses on understand-
ing how diet (1) affects the genome, directly (e.g. via methylation) or indirectly (e.g. at
the gene expression level); (2) may compensate for or accentuate the effect of genetic
polymorphisms; and (3) can alter the risk for disease development by interfering with
the molecular processes involved in disease onset, incidence, progression, and/or sever-
ity. The ultimate goal is the in-depth understanding of the genome–nutrient interaction,
which will lead to carefully targeted dietary intervention strategies for restoring health
and fitness and for preventing diet-related disease. Many studies are beginning to address
the interplay between genome and nutrition, such as in the case of type 2 diabetes (268).
A characteristic example of the importance of nutrigenomic studies lies in the discovery
of a polymorphism in the angiotensinogen gene, which alters the effect of dietary fiber
on human blood pressure. Specifically, individuals with the angiotensinogen TT geno-
type have decreased blood pressure, when provided with high insoluble fiber diets. In
contrast, individuals with the TM or MM genotype do not experience a significant effect
on their blood pressure in response to dietary fiber (269). Similarly, in individuals with a
specific polymorphism in PPARgamma (Pro12Ala), a low polyunsaturated-to-saturated
fat ratio is associated with an increase in body mass index and fasting insulin concentra-
tions, suggesting that when the dietary polyunsaturated-to-saturated fat ratio is low, the
body mass index in Ala carriers is greater than that in Pro homozygotes (270). When the
dietary ratio is high, the opposite is seen. Analysis of 1,120 white subjects in the context
of the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study demon-
strated that common genetic variants at the IL1b locus were associated with risk of
metabolic syndrome and related phenotypes. Importantly, a significant interaction was
identified between dietary polyunsaturated fatty acids, and specifically docosahexaenoic
acids and eicosapentaenoic acids, intake and the IL1b 6054G>A polymorphism, with
AA subjects having significantly lower risk of metabolic syndrome. This suggests that
the increasing genetic predisposition towards the development of metabolic syndrome in
these individuals, could be reduced by a diet rich in polyunsaturated fatty acids, support-
ing the notion that more tailored dietary recommendations could be successfully used
to prevent chronic diseases (131). Furthermore, the Framingham Heart Study, involv-
ing 2,148 participants, identified an APOA5 polymorphism that was associated with
polyunsaturated fatty acid intake in a dose-dependent manner thus determining fasting
triglyceride levels (271).
28 Sanoudou, Vafiadaki, and Mantzoros
5. FUTURE DIRECTIONS
Current technological advances are enabling an unprecedented width and speed of
scientific discovery, thus increasing rapidly our understanding of the genetic etiology of
obesity, metabolic syndrome, and diabetes. Although the number of disease-associated
genes has recently risen sharply, many more yet-to-be-discovered genes are believed to
be implicated in the above-mentioned complex diseases. Better designed, large-scale,
multipopulation meta-analyses are starting to provide the necessary statistical power and
biological breadth to uncover new genetic players in disease development. In parallel to
causative gene mutations and single nucleotide polymorphisms (SNPs – the most com-
mon form of polymorphisms associated with obesity, metabolic syndrome, and diabetes),
new forms of genome variation such as DNA copy number variants or novel mechanisms
of genome/transcriptome regulation, such as microRNAs, are introducing an additional
level of complexity that needs to be considered. Advanced technological tools, together
with cumulative biological knowledge, will allow us to answer the many open questions
in disease pathophysiology such as, for example, the effect of type 1 diabetes genetic
variants in immune response and tolerance or their role on insulin action and β-cell func-
tion in type 2 diabetes. Meanwhile, the long-suspected gene–environment interplay will
be molecularly deciphered through rapidly evolving disciplines such as nutrigenomics.
All this wealth of knowledge should translate in presymptomatic genetic diagnosis and
effective preventive approaches, as well as improved clinical management when disease
development is inevitable. Therapies will be better targeted to specific molecular path-
ways and therefore likely to be more efficient and effective. Ultimately, the advent of
pharmacogenomics will allow the promise of personalized medicine to be fulfilled.
REFERENCES
1. Sorensen TI. The genetics of obesity. Metabolism 1995; 44:4–6.
2. Maes HH, Neale MC, Eaves LJ. Genetic and environmental factors in relative body weight and human
adiposity. Behav. Genet. 1997; 27:325–351.
3. Barsh GS, Farooqi IS, O’Rahilly S. Genetics of body-weight regulation. Nature 2000; 404:644–651.
4. Bluher M. Transgenic animal models for the study of adipose tissue biology. Best Pract. Res. Clin.
Endocrinol. Metabol. 2005; 19:605–623.
5. Leibel RL, Chung WK, Chua SCJ. The molecular genetics of rodent single gene obesities. J. Biol.
Chem 1997; 275:31937–31940.
6. Chagnon YC, Bouchard C. Genetics of obesity: advances from rodent studies. Trends Genet. 1996;
12:441–444.
7. Rankinen T, Zuberi A, Chagnon YC, et al. The human obesity map: the 2005 update. Obesity 2006;
14:529–644.
8. Coll AP, Farooqi IS, Challis BG, Yeo S, O’Rahilly S. Proopiomelanocortin and energy balance: insights
from human and murine genetics. J. Endocrinol. Metab. 2004; 89:2557–2562.
9. Clement K. Genetics of human obesity. Proc. Nutr. Soc. 2005; 64:133–142.
10. Harrold JA, Williams G. Melanocortin-4 receptors, beta-MSH and leptin: key elements in the satiety
pathway. Peptides 2006; 27:365–371.
11. Strobel A, Issad T, Camoin L, Ozata M, Strosberg AD. A leptin missense mutation associated with
hypogonadism and morbid obesity. Nat. Genet. 1998; 18:213–215.
12. Montague CT, Farooqi IS, Whitehead JP, et al. Congenital leptin deficiency is associated with severe
early-onset obesity in humans. Nature 1997; 387:903–90.
13. Ozata M, Ozdemir IC, Licinio J. Human leptin deficiency caused by a missense mutation: multiple
Chapter 2 / Genes and Gene–Environment Interactions 29
endocrine defects, decreased sympathetic tone, and immune system dysfunction indicate new targets
for leptin action, greater central than peripheral resistance to the effects of leptin, and spontaneous
correction of leptin-mediated defects. J. Clin. Endocrinol. Metab. 1999; 84:3686–3695.
14. Clement K, Vaisse C, Lahlou N, et al. A mutation in the human leptin receptor gene causes obesity and
pituitary dysfunction. Nature 1998; 392:398–401.
15. Farooqi IS, Wangensteen T, Collins S, et al. Clinical and molecular genetic spectrum of congenital
deficiency of the leptin receptor. N. Engl. J. Med. 2007; 356:237–247.
16. Challis BG, Pritchard LE, Creemers JW, et al. A missense mutation disrupting a dibasic prohormone
processing site in pro-opiomelanocortin (POMC) increases susceptibility to early-onset obesity through
a novel molecular mechanism. Hum. Mol. Genet. 2002; 11:1997–2004.
17. Krude H, Biebermann H, Luck W, Horn R, Brabant G, Gruters A. Severe early-onset obesity, adrenal insuffi-
ciency and red hair pigmentation caused by POMC mutations in humans. Nat. Genet. 1998; 19:155–157.
18. Jackson RS, Creemers JW, Ohagi S, et al. Obesity and impaired prohormone processing associated
with mutations in the human prohormone convertase 1 gene. Nat. Genet. 1997; 16:303–306.
19. Yeo GS, Farooqi IS, Aminian S, Halsall DJ, Stanhope RG, O’Rahilly S. A frameshift mutation in MC4R
associated with dominantly inherited human obesity. Nat. Genet. 1998; 20:111–112.
20. Vaisse C, Clement K, Guy-Grand B, Froguel P. A frameshift mutation in human MC4R is associated
with a dominant form of obesity. Nat. Genet. 1998; 20:113–114.
21. Hinney A, Schmidt A, Nottebom K, et al. Several mutations in the melanocortin-4 receptor gene includ-
ing a nonsense and a frameshift mutation associated with dominantly inherited obesity in humans.
J. Clin. Endocrinol. Metab. 1999; 84:1483–1486.
22. Gu W, Tu Z, Kleyn PW, et al. Identification and functional analysis of novel human melanocortin-4
receptor variants. Diabetes 1999; 48:635–639.
23. Holder JL, Butte NF, Zinn AR. Profound obesity associated with a balanced translocation that disrupts
the SIM1 gene. Hum. Mol. Genet. 2000; 9:101–108.
24. Yeo GS, Connie Hung CC, Rochford J, et al. A de novo mutation affecting human TrkB associated
with severe obesity and developmental delay. Nat. Neurosci. 2004; 7:1187–1189.
25. Challis BG, Luan J, Keogh J, Wareham NJ, Farooqi IS, O’Rahilly S. Genetic variation in the cortico-
trophin-releasing factor receptors: identification of single-nucleotide polymorphisms and association
studies with obesity in UK Caucasians. Int. J. Obes. Relat. Metab. Disord. 2004; 28:442–446.
26. Gibson WT, Pissios P, Trombly DJ, et al. Melanin-concentrating hormone receptor mutations and hu-
man obesity: functional analysis. Obes. Res. 2004; 12:743–749.
27. Tao YX. Molecular mechanisms of the neural melanocortin receptor dysfunction in severe early onset
obesity. Mol. Cell. Endocrinol. 2005; 239:1–14.
28. Lee YS, Poh LK, Loke KY. A novel melanocortin 3 receptor gene (MC3R) mutation associated with
severe obesity. J. Clin. Endocrinol. Metab. 2002; 87:1423–1326.
29. Rached M, Buronfosse A, Begeot M, Penhoat A. Inactivation and intracellular retention of the hu-
man I183N mutated melanocortin 3 receptor associated with obesity. Biochim. Biophys. Acta. 2004;
1689:229–234.
30. Bell CG, Walley AJ, Froguel P. The genetics of human obesity. Nat. Rev. Genet. 2005; 6:221–234.
31. Farooqi IS, O’Rahilly S. Monogenic obesity in humans. Ann. Rev. Med. 2005; 56:443–458.
32. Hinney A, Bettecken T, Tarnow P, et al. Prevalence, spectrum, and functional characterization of
melanocortin-4 receptor gene mutations in a representative population-based sample and obese adults
from Germany. J. Clin. Endocrinol. Metab. 2006; 91:1761–1769.
33. Lubrano-Berthelier C, Cavazos M, Dubern B, et al. Molecular genetics of human obesity-associated
MC4R mutations. Ann. N.Y. Acad. Sci. 2003; 994:49–57.
34. Huszar D, Lynch CA, Fairchild-Huntress V, et al. Targeted disruption of the melanocortin-4 receptor
results in obesity in mice. Cell 1997; 88:131–141.
35. Ho G, MacKenzie RG. Functional characterization of mutations in melanocortin-4 receptor associated
with human obesity. J. Biol. Chem. 1999; 274:35816–35822.
36. Farooqi IS, Matarese G, Lord GM, et al. Beneficial effects of leptin on obesity, T cell hyporesponsive-
ness and neuroendocrine/metabolic dysfunction of human congenital leptin deficiency. J. Clin. Invest.
2002; 110:1093–1103.
37. Mutch DM, Clement K. Unraveling the genetics of human obesity. PLoS Genet. 2006; 2:1956–1963.
30 Sanoudou, Vafiadaki, and Mantzoros
38. Chung WK, Leibel RL. Molecular physiology of syndromic obesities in humans. Trends Endocrinol.
Metab. 2005; 16:267–272.
39. Gilhuis HJ, van Ravenswaaij CM, Hamel BJ, Gabreels FJ. Interstitial 6q deletion with a Prader–Willi-
like phenotype: a new case and review of the literature. Eur. J. Paediatr. Neurol. 2000; 4:39–43.
40. Stein CK, Stred SE, Thomson LL, Smith FC, Hoo JJ. Interstitial 6q deletion and Prader–Willi-like
phenotype. Clin. Genet. 1996; 49:306–310.
41. Smith A. The diagnosis of Prader–Willi syndrome. J. Paediatr. Child Health 1999; 35:335–337.
42. Goldstone AP. Prader–Willi syndrome: advances in genetics and pathophysiology and treatment. Trends
Endocrinol. Metab. 2004; 15:12–20.
43. Cummings DE, Clement K, Purnell JQ, et al. Elevated plasma ghrelin levels in Prader–Willi syndrome.
Nat. Med. 2002; 8:643–644.
44. Green JS, Parfrey PS, Harnett JD, et al. The cardinal manifestations of Bardet-Biedl syndrome, a form
of Laurence-Moon-Biedl syndrome. New Eng. J. Med. 1989; 321:1002–1009.
45. Beales PL, Elcioglu N, Woolf AS, Parker D, Flinter FA. New criteria for improved diagnosis of Bardet-
Biedl syndrome: results of a population survey. J. Med. Genet. 1999; 36:437–446.
46. Fan Y, Esmail MA, Ansley SJ, et al. Mutations in a member of the Ras superfamily of small GTP-
binding proteins causes Bardet-Biedl syndrome. Nat. Genet. 2004; 36:989–993.
47. Mykytyn K, Braun T, Carmi R, et al. Identification of the gene that, when mutated, causes the human
obesity syndrome BBS4. Nat. Genet. 2001; 28:188–191.
48. Mykytyn K, Nishimura DY, Searby CC, et al. Identification of the gene (BBS1) most commonly involved
in Bardet-Biedl syndrome, a complex human obesity syndrome. Nat. Genet. 2002; 31:435–438.
49. Nishimura DY, Searby CC, Carmi R, et al. Positional cloning of a novel gene on chromosome 16q
causing Bardet-Biedl syndrome (BBS2). Hum. Mol. Genet. 2001; 10:865–874.
50. Li JB, Gerdes JM, Haycraft CJ, et al. Comparative genomics identifies a flagellar and basal body pro-
teome that includes the BBS5 human disease gene. Cell 2004; 117:541–552.
51. Katsanis N, Beales PL, Woods MO, et al. Mutations in MKKS cause obesity, retinal dystrophy and
renal malformations associated with Bardet-Biedl syndrome. Nat. Genet. 2000; 26:67–70.
52. Nishimura DY, Swiderski RE, Searby CC, et al. Comparative genomics and gene expression analysis
identifies BBS9, a new Bardet-Biedl syndrome gene. Am. J. Hum. Genet. 2005; 77:1021–1033.
53. Badano JL, Ansley SJ, Leitch CC, Lewis RA, Lupski JR, Katsanis N. Identification of a novel Bardet-
Biedl syndrome protein, BBS7, that shares structural features with BBS1 and BBS2. Am. J. Hum.
Genet. 2003; 72:650–658.
54. Ansley SJ, Badano JL, Blacque OE, et al. Basal body dysfunction is a likely cause of pleiotropic Bardet-
Biedl syndrome. Nature 2003; 425:628–633.
55. Chiang AP, Beck JS, Yen HJ, et al. Homozygosity mapping with SNP arrays identifies TRIM32, an
E3 ubiquitin ligase, as a Bardet-Biedl syndrome gene (BBS11). Proc. Natl. Acad. Sci. USA 2006;
103:6287–6292.
56. Stoetzel C, Laurier V, Davis EE, et al. BBS10 encodes a vertebrate-specific chaperonin-like protein
and is a major BBS locus. Nat. Genet. 2006; 38:521–524.
57. Stoetzel C, Muller J, Laurier V, et al. Identification of a novel BBS gene (BBS12) highlights the major
role of a vertebrate-specific branch of chaperonin-related proteins in Bardet-Biedl syndrome. Am. J.
Hum. Genet. 2007; 80:1–11.
58. Katsanis N. The oligogenic properties of Bardet-Biedl syndrome. Hum. Mol. Genet. 2004; 13(Spec.
No. 1):R65–R71.
59. Yen HJ, Tayeh MK, Mullins RF, Stone EM, Sheffield VC, Slusarski DC. Bardet-Biedl syndrome genes
are important in retrograde intracellular trafficking and Kupffer’s vesicle cilia function. Hum. Mol.
Genet. 2006; 15:667–677.
60. Nachury MV, Loktev AV, Zhang Q, et al. A core complex of BBS proteins cooperates with the GTPase
Rab8 to promote ciliary membrane biogenesis. Cell 2007; 129:1201–1213.
61. Russell-Eggitt IM, Clayton PT, Coffey R, Kriss A, Taylor DS, Taylor JF. Alstrom syndrome. Report
of 22 cases and literature review. Ophthalmology 1998; 105:1274–1280.
62. Marshall JD, Bronson RT, Collin GB, et al. New Alstrom syndrome phenotypes based on the evaluation
of 182 cases. Arch. Intern. Med. 2005; 165:675–683.
63. Hearn T, Renforth GL, Spalluto C, et al. Mutation of ALMS1, a large gene with a tandem repeat encod-
ing 47 amino acids, causes Alstrom syndrome. Nat. Genet. 2002; 31:79–83.
Chapter 2 / Genes and Gene–Environment Interactions 31
64. Collin GB, Marshall JD, Ikeda A, et al. Mutations in ALMS1 cause obesity, type 2 diabetes and neu-
rosensory degeneration in Alstrom syndrome. Nat. Genet. 2002; 31:74–78.
65. Marshall JD, Hinman EG, Collin GB, et al. Spectrum of ALMS1 variants and evaluation of genotype–
phenotype correlations in Alstrom syndrome. Hum. Mutat. 2007; 28:1114–1123.
66. Hearn T, Spalluto C, Phillips VJ, et al. Subcellular localization of ALMS1 supports involvement of
centrosome and basal body dysfunction in the pathogenesis of obesity, insulin resistance, and type 2
diabetes. Diabetes 2005; 54:1581–1587.
67. Li G, Vega R, Nelms K, et al. A role for Alstrom syndrome protein, alms1, in kidney ciliogenesis and
cellular quiescence. PLoS Genet. 2007; 3:e8.
68. Wuschke S, Dahm S, Schmidt C, Joost HG, Al-Hasani H. A meta-analysis of quantitative trait loci
associated with body weight and adiposity in mice. Int. J. Obes. (Lond.) 2007; 31:829–841.
69. Sanoudou D, Mantzoros C. Genetics of obesity and diabetes. In: Mantzoros C, ed. Obesity and Diabetes.
Totowa: Humana, 2006; 39–67.
70. Hebebrand J, Friedel S, Schauble N, Geller F, Hinney A. Perspectives: molecular genetic research in
human obesity. Obesity Rev. 2003; 4:139–146.
71. Glazier AM, Nadeau JH, Aitman TJ. Finding genes that underlie complex traits. Science 2002;
298:2345–2349.
72. Abate N, Chandalia M, Satija P, et al. ENPPI/PC-I K121Q polymorphism and genetic susceptibility to
type 2 diabetes. Diabetes 2005; 54:1207–1213.
73. Boutin P, Dina C, Vasseur F, et al. GAD2 on chromosome 10p12 is a candidate gene for human obesity.
PLoS Biol. 2003; 1:361–371.
74. Durand E, Boutin P, Meyre D, et al. Polymorphisms in the amino acid transporter solute carrier family
6 (neurotransmitter transporter) member 14 gene contribute to polygenic obesity in French Caucasians.
Diabetes 2004; 53:2483–2486.
75. Dina C, Meyre D, Gallina S, et al. Variation in FTO contributes to childhood obesity and severe adult
obesity. Nat. Genet. 2007; 39:724–726.
76. Scuteri A, Sanna S, Chen WM, et al. Genome-wide association scan shows genetic variants in the FTO
gene are associated with obesity-related traits. PLoS Genet. 2007; 3:e115.
77. Frayling TM, Timpson NJ, Weedon MN, et al. A common variant in the FTO gene is associated with
body mass index and predisposes to childhood and adult obesity. Science 2007; 316:889–894.
78. Gerken T, Girard CA, Tung YC, et al. The obesity-associated FTO gene encodes a 2-oxoglutarate-
dependent nucleic acid demethylase. Science 2007; 318:1469–1472.
79. Mutch DM, Clement K. Genetics of human obesity. Best. Pract. Res. Clin. Endocrinol. Metab. 2006;
20:647–664.
80. Jandacek RJ, Woods SC. Pharmaceutical approaches to the treatment of obesity. Drug Discov. Today
2004; 15:874–880.
81. Wasan KM, Looije NA. Emerging pharmacological approaches to the treatment of obesity. J. Pharma-
ceut. Sci. 2005; 8:259–271.
82. Federation ID. International Diabetes Federation consensus worldwide definition of the metabolic
syndrome. International Diabetes Federation, 2005.
83. Ford ES, Ajani UA, Mokdad AH. The metabolic syndrome and concentrations of C-reactive protein
among U.S. youth. Diabetes Care 2005; 28:878–881.
84. Cameron AJ, Shaw JE, Zimmet PZ. The metabolic syndrome: prevalence in worldwide populations.
Endocrinol. Metab. Clin. North Am. 2004; 33:351–375; table of contents.
85. Edwards KL, Newman B, Mayer E, Selby JV, Krauss RM, Austin MA. Heritability of factors of the
insulin resistance syndrome in women twins. Genet. Epidemiol. 1997; 14:241–253.
86. Carmelli D, Cardon LR, Fabsitz R. Clustering of hypertension, diabetes, and obesity in adult male
twins: same genes or same environments? Am. J. Hum. Genet. 1994; 55:566–573.
87. Chen W, Srinivasan SR, Elkasabany A, Berenson GS. The association of cardiovascular risk factor
clustering related to insulin resistance syndrome (Syndrome X) between young parents and their off-
spring: the Bogalusa Heart Study. Atherosclerosis 1999; 145:197–205.
88. Hong Y, Rice T, Gagnon J, et al. Familial clustering of insulin and abdominal visceral fat: the HERIT
AGE Family Study. J. Clin. Endocrinol. Metab. 1998; 83:4239–4245.
89. Liese AD, Mayer-Davis EJ, Tyroler HA, et al. Familial components of the multiple metabolic syndrome:
the ARIC study. Diabetologia 1997; 40:963–970.
32 Sanoudou, Vafiadaki, and Mantzoros
90. Mayer EJ, Newman B, Austin MA, et al. Genetic and environmental influences on insulin levels and the
insulin resistance syndrome: an analysis of women twins. Am. J .Epidemiol. 1996; 143:323–332.
91. Sweeney L, Brennan A, Mantzoros C. Metabolic syndrome. In: Regensteiner J, Reusc J, Stewart J,
Veves A, eds. Diabetes and Exercise. Totowa: Humana, 2007.
92. Russell JC, Proctor SD. Small animal models of cardiovascular disease: tools for the study of the roles
of metabolic syndrome, dyslipidemia, and atherosclerosis. Cardiovasc. Pathol. 2006; 15:318–330.
93. Freedman BD, Lee EJ, Park Y, Jameson JL. A dominant negative peroxisome proliferator-activated
receptor-gamma knock-in mouse exhibits features of the metabolic syndrome. J. Biol. Chem. 2005;
280:17118–17125.
94. Ortlepp JR, Kluge R, Giesen K, et al. A metabolic syndrome of hypertension, hyperinsulinaemia and
hypercholesterolaemia in the New Zealand obese mouse. Eur. J. Clin. Invest. 2000; 30:195–202.
95. Yamaguchi Y, Yoshikawa N, Kagota S, Nakamura K, Haginaka J, Kunitomo M. Elevated circulating
levels of markers of oxidative-nitrative stress and inflammation in a genetic rat model of metabolic
syndrome. Nitric Oxide 2006; 15:380–386.
96. Qi NR, Wang J, Zidek V, et al. A new transgenic rat model of hepatic steatosis and the metabolic
syndrome. Hypertension 2005; 45:1004–1011.
97. Seda O, Liska F, Krenova D, et al. Dynamic genetic architecture of metabolic syndrome attributes in
the rat. Physiol. Genomics 2005; 21:243–252.
98. van den Brandt J, Kovacs P, Kloting I. Features of the metabolic syndrome in the spontaneously hypertrig-
lyceridemic Wistar Ottawa Karlsburg W (RT1u Haplotype) rat. Metabolism 2000; 49:1140–1144.
99. Kloting I, Kovacs P, van den Brandt J. Sex-specific and sex-independent quantitative trait loci for facets
of the metabolic syndrome in WOKW rats. Biochem. Biophys. Res. Commun. 2001; 284:150–156.
100. Strahorn P, Graham D, Charchar FJ, Sattar N, McBride MW, Dominiczak AF. Genetic determinants
of metabolic syndrome components in the stroke-prone spontaneously hypertensive rat. J. Hypertens.
2005; 23:2179–2186.
101. Sale MM, Woods J, Freedman BI. Genetic determinants of the metabolic syndrome. Curr. Hypertens.
Rep. 2006; 8:16–22.
102. McQueen MB, Bertram L, Rimm EB, Blacker D, Santangelo SL. A QTL genome scan of the metabolic
syndrome and its component traits. BMC Genet. 2003; 4 (Suppl. 1):S96.
103. Arya R, Blangero J, Williams K, et al. Factors of insulin resistance syndrome-related phenotypes are
linked to genetic locations on chromosomes 6 and 7 in nondiabetic Mexican-Americans. Diabetes
2002; 51:841–847.
104. Langefeld CD, Wagenknecht LE, Rotter JI, et al. Linkage of the metabolic syndrome to 1q23–q31
in Hispanic families: the Insulin Resistance Atherosclerosis Study Family Study. Diabetes 2004;
53:1170–1174.
105. Hamet P, Merlo E, Seda O, et al. Quantitative founder-effect analysis of French Canadian families
identifies specific loci contributing to metabolic phenotypes of hypertension. Am. J. Hum. Genet.
2005; 76:815–832.
106. Loos RJ, Katzmarzyk PT, Rao DC, et al. Genome-wide linkage scan for the metabolic syndrome in
the HERITAGE Family Study. J. Clin. Endocrinol. Metab. 2003; 88:5935–5943.
107. Stein CM, Song Y, Elston RC, Jun G, Tiwari HK, Iyengar SK. Structural equation model-based genome
scan for the metabolic syndrome. BMC Genet. 2003; 4 (Suppl. 1):S99.
108. Olswold C, de Andrade M. Localization of genes involved in the metabolic syndrome using multivari-
ate linkage analysis. BMC Genet. 2003; 4 (Suppl. 1):S57.
109. Ng MC, So WY, Lam VK, et al. Genome-wide scan for metabolic syndrome and related quantitative
traits in Hong Kong Chinese and confirmation of a susceptibility locus on chromosome 1q21–q25.
Diabetes 2004; 53:2676–2683.
110. Cai G, Cole SA, Freeland-Graves JH, MacCluer JW, Blangero J, Comuzzie AG. Principal component
for metabolic syndrome risk maps to chromosome 4p in Mexican Americans: the San Antonio Family
Heart Study. Hum. Biol. 2004; 76:651–665.
111. Tang W, Miller MB, Rich SS, et al. Linkage analysis of a composite factor for the multiple meta-
bolic syndrome: the National Heart, Lung, and Blood Institute Family Heart Study. Diabetes 2003;
52:2840–2847.
Chapter 2 / Genes and Gene–Environment Interactions 33
112. Imperatore G, Knowler WC, Pettitt DJ, et al. A locus influencing total serum cholesterol on chromo-
some 19p: results from an autosomal genomic scan of serum lipid concentrations in Pima Indians.
Arterioscler. Thromb. Vasc. Biol. 2000; 20:2651–2656.
113. Krushkal J, Ferrell R, Mockrin SC, Turner ST, Sing CF, Boerwinkle E. Genome-wide linkage analyses
of systolic blood pressure using highly discordant siblings. Circulation 1999; 99:1407–1410.
114. Cheng LS, Davis RC, Raffel LJ, et al. Coincident linkage of fasting plasma insulin and blood pressure
to chromosome 7q in hypertensive Hispanic families. Circulation 2001; 104:1255–1260.
115. An P, Freedman BI, Hanis CL, et al. Genome-wide linkage scans for fasting glucose, insulin, and insulin
resistance in the National Heart, Lung, and Blood Institute Family Blood Pressure Program: evidence
of linkages to chromosome 7q36 and 19q13 from meta-analysis. Diabetes 2005; 54:909–914.
116. Shearman AM, Ordovas JM, Cupples LA, et al. Evidence for a gene influencing the TG/HDL-C ratio
on chromosome 7q32.3-qter: a genome-wide scan in the Framingham study. Hum. Mol. Genet. 2000;
9:1315–1320.
117. Hirschhorn JN, Lohmueller K, Byrne E, Hirschhorn K. A comprehensive review of genetic association
studies. Genet. Med. 2002; 4:45–61.
118. Pollex RL, Hegele RA. Genetic determinants of the metabolic syndrome. Nat. Clin. Pract. Cardiovasc.
Med. 2006; 3:482–489.
119. Barroso I, Gurnell M, Crowley VE, et al. Dominant negative mutations in human PPARgamma associ-
ated with severe insulin resistance, diabetes mellitus and hypertension. Nature 1999; 402:880–883.
120. Barak Y, Nelson MC, Ong ES, et al. PPAR gamma is required for placental, cardiac, and adipose
tissue development. Mol. Cell 1999; 4:585–595.
121. Gurnell M. PPARgamma and metabolism: insights from the study of human genetic variants. Clin.
Endocrinol. (Oxf.) 2003; 59:267–277.
122. Frederiksen L, Brodbaek K, Fenger M, et al. Comment: studies of the Pro12Ala polymorphism of
the PPAR-gamma gene in the Danish MONICA cohort: homozygosity of the Ala allele confers a
decreased risk of the insulin resistance syndrome. J. Clin. Endocrinol. Metab. 2002; 87:3989–3992.
123. Meirhaeghe A, Cottel D, Amouyel P, Dallongeville J. Association between peroxisome proliferator-
activated receptor gamma haplotypes and the metabolic syndrome in French men and women. Diabetes
2005; 54:3043–3048.
124. Phillips C, Lopez-Miranda J, Perez-Jimenez F, McManus R, Roche HM. Genetic and nutrient deter-
minants of the metabolic syndrome. Curr. Opin. Cardiol. 2006; 21:185–193.
125. Dallongeville J, Helbecque N, Cottel D, Amouyel P, Meirhaeghe A. The Gly16 Arg16 and Gln27 Glu27
polymorphisms of beta2-adrenergic receptor are associated with metabolic syndrome in men. J. Clin.
Endocrinol. Metab. 2003; 88:4862–4866.
126. Fernandez ML, Ruiz R, Gonzalez MA, et al. Association of NOS3 gene with metabolic syndrome in
hypertensive patients. Thromb. Haemost. 2004; 92:413–418.
127. Lee YJ, Tsai JC. ACE gene insertion/deletion polymorphism associated with 1998 World Health
Organization definition of metabolic syndrome in Chinese type 2 diabetic patients. Diabetes Care
2002; 25:1002–1008.
128. Jowett JB, Elliott KS, Curran JE, et al. Genetic variation in BEACON influences quantitative variation
in metabolic syndrome-related phenotypes. Diabetes 2004; 53:2467–2472.
129. Steinle NI, Kazlauskaite R, Imumorin IG, et al. Variation in the lamin A/C gene: associations with
metabolic syndrome. Arterioscler. Thromb. Vasc. Biol. 2004; 24:1708–1713.
130. Hamid YH, Rose CS, Urhammer SA, et al. Variations of the interleukin-6 promoter are associated
with features of the metabolic syndrome in Caucasian Danes. Diabetologia 2005; 48:251–260.
131. Shen J, Arnett DK, Peacock JM, et al. Interleukin1beta genetic polymorphisms interact with polyun-
saturated fatty acids to modulate risk of the metabolic syndrome. J. Nutr. 2007; 137:1846–1851.
132. Guettier JM, Georgopoulos A, Tsai MY, et al. Polymorphisms in the fatty acid-binding protein 2 and
apolipoprotein C-III genes are associated with the metabolic syndrome and dyslipidemia in a South
Indian population. J. Clin. Endocrinol. Metab. 2005; 90:1705–1711.
133. Acton S, Osgood D, Donoghue M, et al. Association of polymorphisms at the SR-BI gene locus with
plasma lipid levels and body mass index in a white population. Arterioscler. Thromb. Vasc. Biol. 1999;
19:1734–1743.
34 Sanoudou, Vafiadaki, and Mantzoros
134. Borggreve SE, Hillege HL, Wolffenbuttel BH, et al. The effect of cholesteryl ester transfer protein
-629C A promoter polymorphism on high-density lipoprotein cholesterol is dependent on serum
triglycerides. J. Clin. Endocrinol. Metab. 2005; 90:4198–4204.
135. Hutter CM, Austin MA, Farin FM, et al. Association of endothelial lipase gene (LIPG) haplotypes
with high-density lipoprotein cholesterol subfractions and apolipoprotein AI plasma levels in Japanese
Americans. Atherosclerosis 2006; 185:78–86.
136. Deeb SS, Zambon A, Carr MC, Ayyobi AF, Brunzell JD. Hepatic lipase and dyslipidemia: interactions
among genetic variants, obesity, gender, and diet. J. Lipid. Res. 2003; 44:1279–1286.
137. Srinivasan SR, Li S, Chen W, Boerwinkle E, Berenson GS. R219K polymorphism of the ABCA1 gene
and its modulation of the variations in serum high-density lipoprotein cholesterol and triglycerides
related to age and adiposity in white versus black young adults. The Bogalusa Heart Study. Metabolism
2003; 52:930–934.
138. Lai CQ, Demissie S, Cupples LA, et al. Influence of the APOA5 locus on plasma triglyceride, lipopro-
tein subclasses, and CVD risk in the Framingham Heart Study. J. Lipid Res. 2004; 45:2096–2105.
139. Lifton RP, Gharavi AG, Geller DS. Molecular mechanisms of human hypertension. Cell 2001;
104:545–556.
140. Lang F, Capasso G, Schwab M, Waldegger S. Renal tubular transport and the genetic basis of hyper-
tensive disease. Clin. Exp. Nephrol. 2005; 9:91–99.
141. Jeunemaitre X, Soubrier F, Kotelevtsev YV, et al. Molecular basis of human hypertension: role of
angiotensinogen. Cell 1992; 71:169–180.
142. Nakayama T, Soma M, Takahashi Y, Rehemudula D, Kanmatsuse K, Furuya K. Functional deletion
mutation of the 5¢-flanking region of type A human natriuretic peptide receptor gene and its associa-
tion with essential hypertension and left ventricular hypertrophy in the Japanese. Circ. Res. 2000;
86:841–845.
143. Fornage M, Amos CI, Kardia S, Sing CF, Turner ST, Boerwinkle E. Variation in the region of the
angiotensin-converting enzyme gene influences interindividual differences in blood pressure levels
in young white males. Circulation 1998; 97:1773–1779.
144. O’Donnell CJ, Lindpaintner K, Larson MG, et al. Evidence for association and genetic linkage of the
angiotensin-converting enzyme locus with hypertension and blood pressure in men but not women in
the Framingham Heart Study. Circulation 1998; 97:1766–1772.
145. Hsueh WC, Mitchell BD, Schneider JL, et al. QTL influencing blood pressure maps to the region of
PPH1 on chromosome 2q31–34 in Old Order Amish. Circulation 2000; 101:2810–2816.
146. Izawa H, Yamada Y, Okada T, Tanaka M, Hirayama H, Yokota M. Prediction of genetic risk for hy-
pertension. Hypertension 2003; 41:1035–1040.
147. Yatsu K, Mizuki N, Hirawa N, et al. High-resolution mapping for essential hypertension using mic-
rosatellite markers. Hypertension 2007; 49:446–452.
148. Chang YP, Liu X, Kim JD, et al. Multiple genes for essential-hypertension susceptibility on chromo-
some 1q. Am. J. Hum. Genet. 2007; 80:253–264.
149. Spielman RS, Ewens WJ. The TDT and other family-based tests for linkage disequilibrium and as-
sociation. Am. J. Hum. Genet. 1996; 59:983–989.
150. Qian X, Lu Z, Tan M, Liu H, Lu D. A meta-analysis of association between C677T polymorphism in
the methylenetetrahydrofolate reductase gene and hypertension. Eur. J. Hum. Genet. 2007; 15:1239–
1245.
151. Rapp JP. Genetic analysis of inherited hypertension in the rat. Physiol. Rev. 2000; 80:135–172.
152. Woon PY, Kaisaki PJ, Braganca J, et al. Aryl hydrocarbon receptor nuclear translocator-like (BMAL1)
is associated with susceptibility to hypertension and type 2 diabetes. Proc. Natl. Acad. Sci. USA 2007;
104:14412–14417.
153. Printz MP, Jirout M, Jaworski R, Alemayehu A, Kren V. Genetic models in applied physiology. HXB/
BXH rat recombinant inbred strain platform: a newly enhanced tool for cardiovascular, behavioral,
and developmental genetics and genomics. J. Appl .Physiol. 2003; 94:2510–2522.
154. Kreutz R, Hubner N. Congenic rat strains are important tools for the genetic dissection of essential
hypertension. Semin. Nephrol. 2002; 22:135–147.
155. Kwitek-Black AE, Jacob HJ. The use of designer rats in the genetic dissection of hypertension. Curr.
Hypertens. Rep. 2001; 3:12–18.
Chapter 2 / Genes and Gene–Environment Interactions 35
156. Nabika T, Kobayashi Y, Yamori Y. Congenic rats for hypertension: how useful are they for the hunting
of hypertension genes? Clin. Exp. Pharmacol. Physiol. 2000; 27:251–256.
157. Dominiczak AF, Negrin DC, Clark JS, Brosnan MJ, McBride MW, Alexander MY. Genes and hyper-
tension: from gene mapping in experimental models to vascular gene transfer strategies. Hypertension
2000; 35:164–172.
158. Takahashi N, Smithies O. Gene targeting approaches to analyzing hypertension. J. Am. Soc. Nephrol.
1999; 10:1598–1605.
159. Kurihara Y, Kurihara H, Suzuki H, et al. Elevated blood pressure and craniofacial abnormalities in
mice deficient in endothelin-1. Nature 1994; 368:703–710.
160. Huang PL, Huang Z, Mashimo H, et al. Hypertension in mice lacking the gene for endothelial nitric
oxide synthase. Nature 1995; 377:239–242.
161. Ohuchi T, Kuwaki T, Ling GY, et al. Elevation of blood pressure by genetic and pharmacological
disruption of the ETB receptor in mice. Am. J. Physiol. 1999; 276:R1071–R1077.
162. Cvetkovic B, Sigmund CD. Understanding hypertension through genetic manipulation in mice. Kidney
Int. 2000; 57:863–874.
163. Rohrer DK, Desai KH, Jasper JR, et al. Targeted disruption of the mouse beta1-adrenergic receptor
gene: developmental and cardiovascular effects. Proc. Natl. Acad. Sci. USA 1996; 93:7375–7380.
164. Association AD. Diagnosis and classification of diabetes mellitus. Diabetes Care 2006; 29:S43–
S48.
165. Freeman H, Cox RD. Type-2 diabetes: a cocktail of genetic discovery. Hum. Mol. Genet. 2006;
15:R202–R209.
166. Zimmet P, Alberti KG, Shaw J. Global and societal implications of the diabetes epidemic. Nature
2001; 414:782–787.
167. Gottlieb GS . Diabetes in offspring and siblings of juvenile- and maturity-onset-type diabetes .
J. Chronic. Dis. 1980; 33:331–339.
168. McCarthy MI. Susceptibility gene discovery for common metabolic and endocrine traits. J. Mol.
Endocrinol. 2002; 28:1–17.
169. McCarthy MI, Froguel P. Genetic approaches to the molecular understanding of type 2 diabetes. Am.J.
Physiol. Endocrinol. Metab. 2002; 283:E217–E225.
170. Ueda H, Ikegami H, Yamato E, et al. The NSY mouse: a new animal model of spontaneous NIDDM
with moderate obesity. Diabetologia 1995; 38:503–508.
171. Coleman DL. Lessons from studies with genetic forms of diabetes in the mouse. Metabolism 1983;
32:162–164.
172. Ikeda H. KK mouse. Diabetes. Res. Clin. Pract. 1994; 24:S313–S316.
173. Kawano K, Hirashima T, Mori S, Saitoh Y, Kurosumi M, Natori T. Spontaneous long-term hyperglyc-
emic rat with diabetic complications. Otsuka Long-Evans Tokushima Fatty (OLETF) strain. Diabetes
1992; 41:1422–1428.
174. Goto Y, Kakizaki M. The spontaneous-diabetes rat: a model of noninsulin-dependent diabetes mel-
litus. Proc. Jpn Acad. 1981; 57:381–384.
175. Peterson RG, Shaw WN, Neel M, Little LA, Eichberg J. Zucker diabetic fatty rat as a model for non-
insulin-dependent diabetes mellitus. ILAR J.1990; 32:16–19.
176. Kose H, Moralejo DH, Ogino T, Mizuno A, Yamada T, Matsumoto K. Examination of OLETF-derived
non-insulin-dependent diabetes mellitus QTL by construction of a series of congenic rats. Mamm.
Genome 2002; 13:558–562.
177. Moralejo DH, Wei S, Wei K, Yamada T, Matsumoto K. X-linked locus is responsible for non-insulin-
dependent diabetes mellitus in the OLETF rat. J. Vet. Med. Sci. 1998; 60:373–375.
178. Ueda H, Ikegami H, Kawaguchi Y, et al. Genetic analysis of late-onset type 2 diabetes in a mouse
model of human complex trait. Diabetes 1999; 48:1168–1174.
179. Accili D, Drago J, Lee EJ, et al. Early neonatal death in mice homozygous for a null allele of the
insulin receptor gene. Nat. Genet. 1996; 12:106–109.
180. Joshi RL, Lamothe B, Cordonnier N, et al. Targeted disruption of the insulin receptor gene in the
mouse results in neonatal lethality. EMBO J. 1996; 15:1542–1547.
181. Araki E, Lipes MA, Patti ME, et al. Alternative pathway of insulin signalling in mice with targeted
disruption of the IRS-1 gene. Nature 1994; 372:186–190.
36 Sanoudou, Vafiadaki, and Mantzoros
182. Withers DJ, Gutierrez JS, Towery H, et al. Disruption of IRS-2 causes type 2 diabetes in mice. Nature
1998; 391:900–904.
183. Liu SC, Wang Q, Lienhard GE, Keller SR. Insulin receptor substrate 3 is not essential for growth or
glucose metabolism. J. Biol. Chem. 1999; 274:18093–18099.
184. Fantin VR, Wang Q, Lienhard GE, Keller SR. Mice lacking insulin receptor substrate 4 exhibit mild
defects in growth, reproduction and glucose metabolism. Am. J. Physiol. Endocrinol. Metab. 2000;
278: E127–E133.
185. Brunning JC, Winnay J, Bonner-Weir S, Taylor SI, Accili D, Kahn CR. Development of a novel poly-
genic model of NIDDM in mice heterozygous for IR and IRS-1 null alleles. Cell 1997; 88:561–572.
186. Terauchi Y, Iwamoto K, Tamemoto H, et al. Development of non-insulin-dependent diabetes mellitus
in the double knockout mice with disruption of insulin receptor substrate-1 and beta cell glucokinase
genes. Genetic reconstitution of diabetes as a polygenic disease. J. Clin. Invest. 1997; 99:861–866.
187. Bruning JC, Michael MD, Winnay JN, et al. A muscle specific insulin receptor knockout exhibits
features of the metabolic syndrome of NIDDM without altering glucose tolerance. Mol. Cell 1998;
2:559–569.
188. Michael MD, Kulkarni RN, Postic C, Previs SF, Shulman GI, Magnuson MA. Loss of insulin signal-
ling in hepatocytes leads to severe insulin resistance and progressive hepatic dysfunction. Mol. Cell
2000; 6:87–97.
189. Kulkarni RN, Bruning JC, Winnay JN, Postic C, Magnuson MA, Kahn CR. Tissue-specific knockout
of the insulin receptor in pancreatic beta cells creates an insulin secretory defect similar to that in type
2 diabetes. Cell 1999; 96:329–339.
190. Gloyn AL, Weedon MN, Owen KR, et al. Large-scale association studies of variants in genes encod-
ing the pancreatic beta-cell KATP channel subunits Kir6.2 (KCNJ11) and SUR1 (ABCC8) confirm
that the KCNJ11 E23K variant is associated with type 2 diabetes. Diabetes 2003; 52:568–572.
191. Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN. Meta-analysis of genetic association
studies supports a contribution of common variants to susceptibility to common disease. Nat. Genet.
2003; 33:177–182.
192. Memisoglu A, Hu FB, Hankinson SE, et al. Prospective study of the association between the proline
to alanine codon 12 polymorphism in the PPARgamma gene and type 2 diabetes. Diabetes Care 2003;
26:2915–2917.
193. Deeb SS, Fajas L, Nemoto M, et al. A Pro12Ala substitution in PPARg2 associated with decreased recep-
tor activity, lower body mass index and improved insulin sensitivity. Nat. Genet. 1998; 20:284–287.
194. Hani EH, Boutin P, Durand E, et al. Missense mutations in the pancreatic islet beta cell inwardly
rectifying K+ channel gene (KIR6.2/BIR): a meta-analysis suggests a role in the polygenic basis of
type II diabetes mellitus in Caucasians. Diabetologia 1998; 41:1511–1515.
195. Jellema A, Zeegers MP, Feskents EJ, Dagnelie PC, Mensink RP. Gly972Arg variant in the insulin
receptor substrate-1 gene and association with type 2 diabetes: a meta-analysis of 27 studies. Diabe-
tologia 2003; 46:990–995.
196. Zeggini E, Parkinson JR, Halford S, et al. Association studies of insulin receptor substrate 1 gene
(IRS1) variants in type 2 diabetes samples enriched for family history and early age of onset. Diabetes
2004; 53:3319–3322.
197. Florez JC, Sjogren M, Burtt N, et al. Association testing in 9,000 people fails to confirm the associa-
tion of the insulin receptor substrate-1 G972R polymorphism with type 2 diabetes. Diabetes 2004;
53:3313–3318.
198. Rhodes CJ, White MF. Molecular insights into insulin action and secretion. Eur. J. Clin. Invest. 2002;
32:3–13.
199. Horikawa Y, Oda N, Cox NJ, et al. Genetic variation in the gene encoding calpain-10 is associated
with type 2 diabetes mellitus. Nat. Genet. 2000; 26:163–175.
200. Weedon MN, Schwarz PEH, Horikawa Y, et al. Meta-analysis confirms the role of calpain-10 variation
in type 2 diabetes susceptibility. Am. J. Hum. Genet. 2003; 73:1208–1212.
201. Baier LJ, Permana PA, Yang X, et al. A calpain-10 gene polymorphism is associated with reduced
muscle mRNA levels and insulin resistance. J. Clin. Invest. 2000; 106:R69–R73.
202. Sreenan SK, Zhou YP, Otani K, et al. Calpains play a role in insulin secretion and action. Diabetes 2001;
50:2013–2020.
Chapter 2 / Genes and Gene–Environment Interactions 37
203. Tripathy D, Eriksson KF, Orho-Melander M, Fredriksson J, Ahlqvist G, Groop L. Parallel manifesta-
tion of insulin resistance and beta cell decompensation is compatible with a common defect in type
2 diabetes. Diabetologia 2004; 47:782–793.
204. Sladek R, Rocheleau G, Rung J, et al. A genome-wide association study identifies novel risk loci for
type 2 diabetes. Nature 2007; 445:881–885.
205. Grant SF, Thorleifsson G, Reynisdottir I, et al. Variant of transcription factor 7-like 2 (TCF7L2) gene
confers risk of type 2 diabetes. Nat. Genet. 2006; 38:320–323.
206. Scott LJ, Mohlke KL, Bonnycastle LL, et al. A genome-wide association study of type 2 diabetes in
Finns detects multiple susceptibility variants. Science 2007; 316:1341–1345.
207. Meyre D, Lecoeur C, Delplanque J, et al. Variants of ENPP1 are associated with childhood and
adult obesity and increase the risk of glucose intolerance and type 2 diabetes. Nat. Genet. 2005;
37:863–867.
208. McCarthy MI, Zeggini E. Genetics of type 2 diabetes. Curr. Diabetes Rep. 2006; 6:147–154.
209. Zeggini E, Weedon MN, Lindgren CM, et al. Replication of genome-wide association signals in UK
samples reveals risk loci for type 2 diabetes. Science 2007; 316:1336–1341.
210. Diabetes Genetics Initiative of Broad Institute of Harvard and MIT, LU and NIoBR: Saxena R, Voight
BF, et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels.
Science 2007; 316:1331–1336.
211. Frayling TM, McCarthy MI. Genetic studies of diabetes following the advent of the genome-wide
association study: where do we go from here? Diabetologia 2007; 50:2229–2233.
212. Mootha VK, Lindgren CM, Eriksson KF, et al. PGC-1alpha-responsive genes involved in oxidative
phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 2003; 34:267–273.
213. Bino RJ, Hall RD, Fiehn O, et al. Potential of metabolomics as a functional genomics tool. Trends
Plant Sci. 2004; 9:418–425.
214. Griffin JL, Nicholls AW. Metabolomics as a functional genomics tool for understanding lipid dysfunc-
tion in diabetes, obesity and related disorders. Pharmacogenomics 2006; 7:1095–1107.
215. Wang C, Kong H, Guan Y, et al. Plasma phospholipid metabolic profiling and biomarkers of type 2
diabetes mellitus based on high-performance liquid chromatography/electrospray mass spectrometry
and multivariate statistical analysis. Anal. Chem. 2005; 77:4108–4116.
216. Yang J, Xu G, Hong Q, et al. Discrimination of type 2 diabetic patients from healthy controls by using
metabonomics method based on their serum fatty acid profiles. J. Chromatogr. B. Anal. Technol. Biomed.
Life. Sci. 2004; 813:53–58.
217. Tattersall RB, Fajans SS. A difference between the inheritance of classical juvenile-onset and maturity
onset type of diabetes in young people. Diabetes 1975; 24:44–53.
218. Yamagata K, Furuta H, Oda N, et al. Mutations in the hepatocyte nuclear factor-4a gene in the maturity-
onset diabetes of the young (MODY1). Nature 1996; 384:458–460.
219. Yamagata K, Oda N, Kaisaki PJ, et al. Mutations in the hepatocyte nuclear factor-1a gene in maturity-
onset diabetes of the young (MODY3). Nature 1996; 384:455–458.
220. Vionnet N, Stoffel M, Takeda J, et al. Nonsense mutation in the glucokinase gene causes early-onset
non-insulin-dependent diabetes mellitus. Nature 1992; 356:721–722.
221. Stoffers DA, Ferrer J, Clarke WL, Habener JF. Early onset type-II diabetes mellitus (MODY4) linked
to IPF1. Nat. Genet. 1997; 17:138–139.
222. Malecki MT, Jhala US, Antonellis A, et al. Mutations in NEUROD1 gene are associated with the
development of type 2 diabetes mellitus. Nat Genet. 1999; 23:323–328.
223. Horikawa Y, Iwasaki N, Hara M, et al. Mutation in hepatocyte nuclear factor-1 beta gene (TCF2)
associated with MODY. Nat. Genet. 1997; 17:384–385.
224. Barroso I. Genetics of type 2 diabetes. Diabetes 2005; 22:517–535.
225. Shih D, Stoffel M. Molecular etiologies of MODY and other early-onset forms of diabetes. Curr.
Diabetes. Rep. 2002; 2:125–134.
226. Velho G, Robert JJ. Maturity-onset diabetes of the young (MODY): genetic and clinical characteristics.
Horm. Res. 2002; 57:29–33.
227. Shimomura H, Sanke T, Hanabusa T, Tsunoda K, Furuta H, Nanjo K. Nonsense mutation of islet-1
gene (Q310X) found in a type 2 diabetic patient with strong family history. Diabetes 2000; 49:1597–
1600.
38 Sanoudou, Vafiadaki, and Mantzoros
228. Huopio H, Otonkoski T, Vauhkonen I, Reimann F, Ashcroft FM, Laakso M. A new subtype of au-
tosomal dominant diabetes attributable to a mutation in the gene for sulfonylurea receptor 1. Lancet
2003; 361:301–307.
229. van den Ouweland JM, Lemkes HH, Ruitenbeek W, et al. Mutation in mitochondrial tRNA(Leu)
(UUR) gene in a large pedigree with maternally transmitted type II diabetes mellitus and deafness.
Nat. Genet. 1992; 1:368–371.
230. Maassen JA, Kadowaki T. Maternally inherited diabetes and deafness: a new diabetes subtype. Dia-
betologia 1996; 39:375–382.
231. Goto Y, Nonaka I, Horai S. A mutation in the tRNA(-Leu)(UUR) gene associated with the MELAS
subgroup of mitochondrial encephalomyopathies. Nature 1990; 348:651–653.
232. Malecki MT. Genetics of type 2 diabetes mellitus. Diabetes. Res. Clin. Pract. 2005; 68 (Suppl. 1):S10–
S21.
233. Genuth S, Alberti KG, Bennett P, et al. Follow-up report on the diagnosis of diabetes mellitus. Diabetes
Care 2003; 26:3160–3167.
234. Gillespie KM. Type 1 diabetes: pathogenesis and prevention. CMAJ 2006; 175:165–170.
235. Onkamo P, Vaananen S, Karnoven M, Tuomilehto J. Worldwide increase in incidence of type I dia-
betes – the analysis of the data on published incidence trends. Diabetologia 1999; 42:1395–1403.
236. Maier LM, Smyth DJ, Vella A, et al. Construction and analysis of tag single nucleotide polymorphism
maps for six human-mouse orthologous candidate genes in type 1 diabetes. BMC Genet. 2005; 6:9.
237. Eisenbarth GS. Animal models of type 1 diabetes: genetics and immunological function. In: Eisenbarth
GS, ed. Type 1 Diabetes: Molecular, Cellular and Clinical Immunology. New York: Kluwer, 2004,
pp. 91–108.
238. Pugliese A, Eisenbarth GS. Type 1 diabetes mellitus of man: genetic susceptibility and resistance.
Adv. Exp. Med. Biol. 2004; 552:170–203.
239. Smyth DJ, Cooper JD, Bailey R, et al. A genome-wide association study of nonsynonymous SNPs
identifies a type 1 diabetes locus in the interferon-induced helicase (IFIH1) region. Nat. Genet. 2006;
38:617–619.
240. Nerup J, Platz P, Andersen OO, et al. HLA antigens and diabetes mellitus. Lancet 1974; 2:864–866.
241. Cudworth AG, Woodworth JC. HLA system and diabetes mellitus. Diabetes 1975; 24:345–349.
242. Nejentsev S, Howson JM, Walker NM, et al. Localization of type 1 diabetes susceptibility to the MHC
class I genes HLA-B and HLA-A. Nature 2007; 450:887–892.
243. Eisenbarth GS, Gottlieb PA. Autoimmune polyendocrine syndromes. N. Engl. J. Med. 2004;
350:2068–2079.
244. Bell GI, Horita S, Karam JH. A polymorphic locus near the insulin gene is associated with insulin-
dependent diabetes mellitus. Diabetes 1984; 33:176–183.
245. Bennett ST, Lucassen AM, Gough SCL, et al. Susceptibility to human type 1 diabetes at IDDM2
is determined by tandem repeat variation at the insulin gene minisatellite locus. Nat. Genet. 1995;
9:284–292.
246. Bottini N, Musumeci L, Alonso A, et al. A functional variant of lymphoid tyrosine phosphatase is
associated with type I diabetes. Nat. Genet. 2004; 36:337–338.
247. Vella A, Cooper JD, Lowe CE, et al. Localization of a type 1 diabetes locus in the IL2RA/CD25 region
by use of tag single-nucleotide polymorphisms. Am. J. Hum. Genet. 2005; 76:773–779.
248. Ueda H, Howson JM, Esposito L, et al. Association of the T-cell regulatory gene CTLA4 with sus-
ceptibility to autoimmune disease. Nature 2003; 423:506–511.
249. Hakonarson H, Grant SF, Bradfield JP, et al. A genome-wide association study identifies KIAA0350
as a type 1 diabetes gene. Nature 2007; 448:591–594.
250. Wicker LS, Miller BJ, Coker LZ, et al. Genetic control of diabetes and insulitis in the nonobese diabetic
(NOD) mouse. J. Exp. Med. 1987; 165:1639–1654.
251. Mein CA, Esposito L, Dunn MG, et al. A search for type 1 diabetes susceptibility genes in families
from the United Kingdom. Nat. Genet. 1998; 19:297–300.
252. Concannon P, Erlich HA, Julier C, et al. Evidence for susceptibility loci from four genomic-wide
linkage scans in 1,435 multiplex families. Diabetes 2005; 54:2995–3001.
253. Concannon P, Gogolin-Ewens KJ, Hinds DA, et al. A second-generation screen of the human genome
for susceptibility to insulin-dependent diabetes mellitus. Nat. Genet. 1998; 19:292–296.
Chapter 2 / Genes and Gene–Environment Interactions 39
254. Todd JA, Walker NM, Cooper JD, et al. Robust associations of four new chromosome regions from
genome-wide analyses of type 1 diabetes. Nat. Genet. 2007; 39:857–864.
255. Smink LJ, Helton EM, Healy BC, et al. T1DBase, a community Web-based resource for type 1 diabetes
research. Nucleic Acids Res. 2005; 33:D544–D549.
256. Hulbert EM, Smink LJ, Adlem EC, et al. T1DBase: integration and presentation of complex data for
type 1 diabetes research. Nucleic Acid Res. 2007; 35(Database issue):D742–D746.
257. Hyoty H. Enterovirus infections and type I diabetes. Ann. Med. 2002; 34:138–147.
258. Honeyman MC, Coulson BS, Stone NL, et al. Association between rotavirus infection and pancreatic
islet autoimmunity in children at risk of developing type 1 diabetes. Diabetes 2000; 49:1319–1324.
259. Tuomi T. Type 1 and type 2 diabetes: what do they have in common? Diabetes 2005; 54:S40–S45.
260. Wilkin TJ. The accelerator hypothesis: weight gain as the missing link between type I and type II
diabetes. Diabetologia 2001; 44:914–922.
261. Hill JO. Understanding and addressing the epidemic of obesity: an energy balance perspective. Endocr.
Rev. 2006; 27:750–761.
262. Sharma V, McNeill JH. The etiology of hypertension in the metabolic syndrome part two: the gene–
environment interaction. Curr. Vasc. Pharmacol. 2006; 4:305–320.
263. Wareham NJ, Franks PW, Harding AH. Establishing the role of gene–environment interactions in the
etiology of type 2 diabetes. Endocrinol. Metab. Clin. North. Am. 2002; 31:553–566.
264. Karnehed N, Tynelius P, Heitmann BL, Rasmussen F. Physical activity, diet and gene–environment
interactions in relation to body mass index and waist circumference: the Swedish young male twins
study. Public Health Nutr. 2006; 9:851–858.
265. Grarup N, Andersen G. Gene–environment interactions in the pathogenesis of type 2 diabetes and
metabolism. Curr. Opin. Clin. Nutr Metab. Care 2007; 10:420–426.
266. Poulsen P, Vaag A, Kyvik K, Beck-Nielsen H. Genetic versus environmental aetiology of the metabolic
syndrome among male and female twins. Diabetologia 2001; 44:537–543.
267. Rankinen T, Church T, Rice T, et al. Effect of endothelin 1 genotype on blood pressure is dependent
on physical activity or fitness levels. Hypertension 2007; 50:1120–1125.
268. Kaput J, Dawson K. Complexity of type 2 diabetes mellitus data sets emerging from nutrigenomic
research: a case for dimensionality reduction? Mutat. Res. 2007; 622:19–32.
269. Hegele RA, Harris SB, Hanley AJ, Sun F, Connelly PW, Zinman B. Angiotensinogen gene variation
associated with variation in blood pressure in aboriginal Canadians. Hypertension 1997; 29:1073–
1077.
270. Luan J, Browne PO, Harding AH, et al. Evidence for gene–nutrient interaction at the PPARgamma
locus. Diabetes 2001; 50:686–689.
271. Lai CQ, Corella D, Demissie S, et al. Dietary intake of n-6 fatty acids modulates effect of apolipo-
protein A5 gene on plasma fasting triglycerides, remnant lipoprotein concentrations, and lipoprotein
particle size: the Framingham Heart Study. Circulation 2006; 113:2062–2070.
272. Meyre D, Delplanque J, Chèvre JC, Lecoeur C, et al. Genome-wide association study for early-onset
and morbid adult obesity identifies three new risk loci in European populations. Nat. Genet. 2009;
41:157–159.
273. Willer CJ, Speliotes EK, Loos RJ, et al. Six new loci associated with body mass index highlight a
neuronal influence on body weight regulation. Nat. Genet. 2009; 41:25–34.
274. Lyssenko V, Nagorny CL, Erdos MR, et al. Common variant in MTNR1B associated with increased
risk of type 2 diabetes and impaired early insulin secretion. Nat. Genet. 2009; 41(1):82–88.
275. Lowe CE, Cooper JD, Brusko T, et al. Large-scale genetic fine mapping and genotype-phenotype
associations implicate polymorphism in the IL2RA region in type 1 diabetes. Nat. Genet. 2007;
39:1074–1082.
276. Wang CY, Podolsky R, She JX. Genetic and functional evidence supporting SUMO4 as a type 1
diabetes susceptibility gene. Ann. N. Y. Acad. Sci. 2006; 1079:257–267.
277. Guo D, Li M, Zhang Y, et al. A functional variant of SUMO4, a new I kappa B alpha modifier, is
associated with type 1 diabetes. Nat. Genet. 2004; 36:837–841.
278. Concannon P, Chen WM, Julier C, et al. Genome-wide scan for linkage to type 1 diabetes in 2,496
multiplex families from the Type 1 Diabetes Genetics Consortium. Diabetes 2009; Jan 9. [Epub ahead
of print]
3 Environmental Inputs, Intake of
Nutrients, and Endogenous Molecules
Contributing to the Regulation
of Energy Homeostasis
Theodore Kelesidis, Iosif Kelesidis,
and Christos S. Mantzoros
KEY POINTS
• In the last 20 years the rapid increase in obesity and associated pathologies in developed
countries has been accompanied by intensification of research efforts and subsequently a
substantial increase in the knowledge of the physiological and molecular mechanisms regulat-
ing body mass.
• These efforts have resulted in the recent discovery of new peripheral hormonal signals as well
as new neuropeptides, involved in body-weight homeostasis.
• This review summarizes new research findings in the area of energy balance regulation, starting
from the original classical hypotheses proposing metabolite sensing, through peripheral
tissue–brain interactions, and coming full circle to the recently discovered pathways regulat-
ing energy homeostasis.
• Understanding these molecular mechanisms will provide new pharmacological targets for the
treatment of obesity and eating disorders and associated comorbidities.
Key Words: Body-weight homeostasis, Energy balance regulation, Obesity, Eating disorders
1. INTRODUCTION
The incidences of both obesity and type 2 diabetes mellitus are rising at epidemic
proportions and have emerged as a major threat to human health in the late twentieth
and early twenty-first century. Growing evidence suggests that nutrient and hormonal
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros (ed.), DOI: 10.1007/978-1-60327-453-1_3,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
41
42 Kelesidis, Kelesidis, and Mantzoros
signals converge and act directly on brain centers, leading to changes in fuel metabolism.
Many newly discovered molecules that are proposed to play an active role in the physi-
ology and pathophysiology of energy homeostasis have changed our understanding
of obesity and metabolism and have attracted the attention of many researchers who
strive to investigate and characterize the mechanisms underlying energy homeostasis.
The purpose of this chapter is to summarize our current understanding of peripheral
pathways regulating energy homeostasis and to outline new targets for the treatment of
obesity, metabolic disorders, and associated comorbidities.
2. INPUTS IMPORTANT IN THE REGULATION OF ENERGY
HOMEOSTASIS
Afferent signals to the brain convey information via exogenous and/or environmen-
tal factors influencing energy homeostasis, nutrients or metabolic factors, and finally
hormonal signals regarding long- or short-term energy availability. These inputs can be
classified into three distinct types, namely, neural environmental, nutrient/metabolic,
and endocrine signals.
2.1. Exogenous Inputs–Environmental Signals
In modern societies of affluence, high palatability and orosensory properties of
certain foods, in combination with environmental influences that promote a sedentary
way of life, promote a positive energy balance and development of obesity. Mood and
other signals that affect “emotional eating” and are being processed by complex neu-
ral circuits have a significant effect on these environmental signals and also regulate
energy homeostasis.
2.2. Metabolic Signals
Sensors expressed in hypothalamic neurons such as ion channels (1,2) and surface
enzymes (3) act as direct sensors of nutrients such as carbohydrates and lipids and activate
intracellular second messenger pathways to regulate energy homeostasis. The role of nutrients
and metabolic signals to regulate energy homeostasis is discussed in detail below.
2.3. Endocrine Signals
Hormones are released from peripheral endocrine organs, including the white adipose
tissue (leptin), pancreas (insulin, amylin), stomach (ghrelin), and intestine (cholecystokinin,
CCK). Hormonal signals such as the adipose-tissue-secreted hormone leptin and the
pancreatic hormone insulin regulate the long-term metabolic status and body’s energy
stores whereas other signals such as gastrointestinal hormones convey information on
the amount or composition of the food entering the gastrointestinal tract.
2.4. Neural Signals
Short-term regulation of feeding is also regulated by neural afferent signals from
the periphery which are activated by a combination of mechanical stimuli (distension,
contraction) (4), chemical stimuli (presence of nutrients in the gut lumen), and neuro-
humoral stimuli (gut hormones, neurotransmitters) (5) and are mainly conveyed via the
vagus nerve to important CNS target centers such as the hypothalamus and the brain
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 43
stem. The central integration of exogenous, environmental metabolic and peripherally
secreted molecules by the CNS is discussed in detail in the subsequent chapter.
3. ENVIRONMENTAL INPUTS
The rapidly changing environment and the associated lifestyle changes are increas-
ingly recognised as one of the primary causes of obesity in western nations (6).The impact
of the environment on energy balance seems to be unidirectional; modern lifestyle
promotes sedentary rather than physically active pursuits and thus positive rather than
negative energy balance (7–9). Variations in the specific set of susceptibility genes
of individuals determine the physiological impact of particular factors by which life-
style and the environment influence energy balance (10) and subsequently individual
susceptibility to obesity and the metabolic syndrome. Hill et al. (11) proposed that sus-
ceptibility to developing obesity could be due to metabolic susceptibility (e.g., tendency
to store rather than burn excess body fat, differences in skeletal muscle composition),
and/or to behavioral susceptibility (tendency to overeat or to be sedentary). The fact
that obesity rates have been gradually increasing might also suggest that people with
a high metabolic susceptibility are experiencing weight gain first as the environment
becomes more obesigenic (i.e., increased food availability, high energy dense food
supply, decreased need for physical activity).
How are exogenous–environmental inputs contributing to the regulation of energy
homeostasis? It is important to recognize the existence of at least two influential systems.
First a central neural network stretching from the hypothalamus to the caudal medulla,
responsive to leptin and other peripherally secreted signals conveying information on
energy and metabolic status, has been identified as the homeostatic control system for
the regulation of food intake and energy balance. This system acts as an integrative
metabolic sensor generating output signals to control energy intake and expenditure in a
coordinated fashion (see subsequent chapter on central regulation of energy homeostasis).
While this system is remarkably powerful in defending the lower limits of adiposity, it
is apparently very weak in curbing appetite in a world of affluence.
Alongside the above-mentioned homeostatic neural system operates another neural
non-homeostatic, “hedonic” system that processes appetite, sensory inputs, and reward-
ing aspects of food intake, ultimately resulting in increased energy intake in genetically
predisposed individuals. Food palatability may have an independent effect and/or interact
with a number of neurotransmitter systems (including dopamine (12), serotonin (13),
and endorphins (12,14,15)) that contribute to appetite, reward, and mood regulation.
Although it is not well understood how the reward value of pleasurable taste and flavor
guides ingestive behavior, psychological components that translate reward into learning,
liking, and wanting more food play a very important role in the pathogenesis of obesity
and have been outlined in recent reports (16).
A further question is whether these systems operate independently of each other
or whether they may interact. Recent finding suggest a role for nucleus accumbens–
hypothalamic pathways in the interaction between the “cognitive” and “emotional” brain
and the “metabolic” brain and thus between non-homeostatic and homeostatic factors
that control food intake (17–21); however, more studies are clearly needed to elucidate
these mechanisms.
44 Kelesidis, Kelesidis, and Mantzoros
3.1. Orosensory Properties of Food
The orosensory properties of food, mainly mediated by palatability, play a significant
role in regulating eating. On a moment-to-moment basis, eating is controlled predominantly
by the orosensory effects of food such as taste, flavor, aroma, and texture of food that pro-
vide positive feedback, and the postingestive effects that provide negative feedback. The
effects of entry of palatable food in the mouth are stimulatory, while the entry of food into
the stomach is inhibitory (22). Thus, heightened responsiveness to hedonic factors, includ-
ing increased palatability, is often cited as a major factor in the development of obesity,
but more needs to be learned in this field and this area is currently the focus of intensive
research efforts (23).
3.2. Emotional Eating
Both appetite and food preferences are altered across a range of mood states; prefer-
ence for “junk food” and increased caloric intake is enhanced during negative mood
states whereas preference for healthier foods is increased during positive mood states (24).
Numerous associations between mood states and emotional eating have been reported
(25), and stress-associated eating (i.e., emotional eating) is more common in those who
are overweight or obese. Various psychological theories of emotional eating have been
proposed (26,27), most of which conclude that emotional eating fails to produce any
lasting benefit to psychological and mood states.
In summary, eating behavior links the internal world of molecules and physiological
processes with the external world of physical and cultural systems. The extent to which
human eating patterns are a function of physiological or environmental pressure is not
always clear. Understanding the pathways responsible for the neural control of feeding and
how the integration of diverse signaling systems could be translated into the expression
of behavior and the accompanying subjective feelings is deemed to be important for the
development of behavioral strategies and pharmacological therapies against obesity.
4. NUTRIENTS
Development of obesity and type 2 diabetes could ensue from alteration in the bal-
ance in the nutrient-activated mechanisms/nutrient-sensing pathways (28). It has been
proposed that circulating factors, e.g., lipids, glucose, or protein products, that are gener-
ated in proportion to body fat stores and/or nutritional status act as signals to the brain,
eliciting changes in energy intake and expenditure (29). A prolonged period of excessive
food intake has been proposed to lead to weight gain and insulin resistance by activat-
ing nutrient-sensing pathways which process the signal for the availability of nutrients
at central sites (hypothalamus) as well as directly in peripheral tissues (muscle and fat).
All these pathways may either act independently or converge to decrease expression of
proliferator-activated receptor coactivator 1 (PGC-1) α and β, key coactivators of PPAR
α, γ, and δ, leading to mitochondrial dysfunction and reduced energy expenditure, all of
which enhance the risk for obesity and insulin resistance (30).
We will further discuss the role of fatty acid metabolism in regulation of energy
homeostasis, since very recent modalities for treating obesity are based on this metabolic
pathway. We will then review the role of dietary fat and dietary carbohydrates in regulating
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 45
body weight, since diet, including low fat or low carbohydrate diets, still remain the
most important therapeutic modality for weight loss.
4.1. The Role of Fatty Acid Metabolism in Regulation
of Energy Homeostasis
A potential role in the regulation of energy balance for fatty acid metabolism act-
ing in the brain or in the periphery has been considered only recently. Several studies
indicate that inhibition of FAS, the enzyme that catalyzes the synthesis of long-chain
fatty acids, using either cerulenin, a natural FAS inhibitor, or synthetic FAS inhibitors,
reduces food intake and causes profound and reversible weight loss (31–38). Through
central, peripheral, or combined central and peripheral mechanisms, these compounds
increase energy consumption to augment weight loss (39). Centrally, these compounds
reduce the expression of orexigenic peptides (40). In vitro and in vivo studies indicate
that, at least in part, C75’s effect is mediated by modulation of adenosine-monophos-
phate-activated protein kinase (AMPK), a member of an energy-sensing kinase family
(41,42). These compounds, with chronic treatment, also alter gene expression peripher-
ally to favor a state of enhanced energy consumption (36,37). While the question of the
physiological role of fatty acid metabolism remains to be fully elucidated, these effects
raise the possibility that pharmacological alterations targeting molecules important in
fatty acid synthesis/degradation may prove to be useful targets for obesity therapeutics.
4.2. The Role of Dietary Fat in the Regulation of Energy Homeostasis
Dietary fat is the most energy-dense macronutrient in the diet (43). Short-term feed-
ing studies have indicated that dietary fat might be used more efficiently than carbohy-
drates and thus it accumulates as body fat (44). When these short-term feeding studies
are extended to 4 days, however, no difference in stored energy is observed (44,45). It
has thus been suggested that carbohydrate intake, unlike fat intake, is regulated (46).
The rationale underlying the promotion of low-fat diets is largely based on the belief that
dietary fat is positively associated with body fat through the high energy density of fat
and enhanced palatability of high-fat foods (43). However, traditional recommendations
of fat restriction have been shown to have a negligible effect on long-term weight loss
(43) whereas low-fat diets may also not offer any benefit in terms of reducing the risk of
cardiovascular disease (47). Thus, further studies are needed to clarify the role of dietary
fat in regulation of energy homeostasis.
4.3. The Role of Dietary Carbohydrates in Regulation of Energy
Homeostasis
Recent studies indicate that low-carbohydrate diets might be more effective for short-
term weight loss than low-fat diets, although this has not been verified by longer-term
studies (48). Weight loss while following a low-carbohydrate diet is thought to result from
a combination of factors: the satiating effect of protein (49), increased energy expenditure
(50,51), appetite suppression from ketosis, as well as restriction of food choice (52–60).
More research is needed to fully define the exact role of low carbohydrate diet in the long-
term regulation of body weight, and to elucidate the underlying mechanisms.
46 Kelesidis, Kelesidis, and Mantzoros
5. HORMONES
Hormonal systems serve as peripheral signals to CNS to provide information regard-
ing energy storage and metabolic state. These hormones deriving mainly from the adi-
pose tissue, the gastrointestinal tract, and the pancreas contribute to the homeostatic
control system for the regulation of food intake and energy balance.
5.1. Adipose Tissue – Adipokines
Adipocytes are active endocrine cells that secrete numerous proteins and bioactive
peptides known as adipokines, which act at both the local (paracrine/autocrine) and
systemic (endocrine) level. The adipose tissue is therefore considered today as a true
endocrine organ (see Table 1 and Fig. 1) (61). The most intensively studied and cur-
Table 1
The Adipose Tissue as an Endocrine Organ: Molecules Secreted by Adipose Tissue
Category Molecules
Hormones Leptin, adiponectin, resistin, estrogens, angiotensino-
gen, retinol binding protein 4, visfatin, apelin
Cytokines IL-6, TNF-α
Complement factors Adipsin (complement factor D), complement C3,
complement factor B, ASP
Extracellular matrix proteins Type I, II, IV, VI collagen, fibronectin, osteonectin,
laminin, entactin, matrix metalloproteinases 2 and 9
Other immune-related proteins MCP-1
Proteins of the RAS Renin, AGT, AT1, AT2, ACE
Acute phase response proteins α1-acid glycoprotein, haptoglobin
Proteins involved in the fibrino- PAI-1, tissue factor
lytic system
Enzymes and transporters LPL, CETP Apolipoprotein E, Adipocyte fatty acid
involved in Lipid metabolism binding protein, CD36.
Enzymes and transporters Insulin receptor substrate 1,2, Phosphatidylinositol 3-ki-
involved in glucose metabolism nase, protein kinase B (Akt), GLUT4, protein kinase λ/ζ
Enzymes involved in steroid Cytochome-P450-dependent aromatase, 17βHSD,
metabolism 11βHSD1
Receptors of peptides and Insulin, glucagon, thyroid-stimulating hormone, growth
glycoproteins hormone, angiotensin-II, gastrin/cholecystokinin B,
adiponectin
Receptors of cytokines IL-6, TNF-α, leptin
Nuclear receptors PPARγ, glucocorticoid, estrogen, progesterone, androgen,
thyroid, vitamin D, nuclear factor-kB
Other Prostacyclin, FFAs
Il-6 interleukin 6, TNF tumor necrosis factor, MCP-1 monocyte chemoatractant protein 1, ASP acylation
stimulating protein, 11bHSD-1 11b-hydroxysteroid dehydrogenase type 1, 17bHSD 17b-hydroxysteroid
dehydrogenase, LPL lipoprotein lipase, CETP cholesterol ester transfer protein, AGT angiotensinogen,
AT1 and 2 angiotensin receptor type 1 and 2, ACE angiotensin-converting enzyme, PAI-1 plasminogen
activator inhibitor, FFAs free fatty acids, PPARγ peroxisome proliferator-activated receptor gamma
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 47
Coagulation factors,
PAI-1, TF
Cardiovascular
diseases Hypertension
Adiponectin
PAI-1
HB-EGF Angiotensinogen Reproduction
Energy balance,
Reproduction
Leptin
Leptin
Glucose Androgen
Metabolism Adipocytes Estrogen
TNF-a
resistin
FFA
Unknown factors
IL-1b, IL-6, IL-8,
LPL, CETP, Apo E IL-18, TGFb
Lipid TNF-a
Acylation stimulating factor
Metabolism Adipsin,
Immune
Complement
function
factors
Fig. 1. Integration of environmental and peripheral signals by the central nervous system.
rently considered most important molecules secreted by the adipose tissue are leptin,
adiponectin, and interleukin-6 (IL-6), which are discussed below.
5.1.1. Leptin
Leptin, a 16-kDa protein, is the product of the ob (leptin) gene. Its discovery has changed
the concept of white adipose tissue from that of an inert tissue to that of an active endocrine
organ. Leptin is expressed predominantly in adipocytes (62) but has also been found in
the hypothalamus, pituitary, placenta, skeletal muscle, and the gastrointestinal tract (63).
Leptin circulates in the blood stream in a free and a bound form, and mediates its meta-
bolic effects by binding to and activating the long isoform of a specific receptor known
as ObRb (64). Signaling pathways downstream of leptin include the JAK STAT pathway,
MAP kinase, and PI3 kinase (65). Leptin levels decrease in response to caloric restric-
tion (66) and they increase in response to overfeeding irrespective of adipose tissue mass.
Leptin secretion is also increased by insulin, glucocorticoids, tumor necrosis factor alpha,
and estrogens, and is decreased in response to starvation (67), β3-adrenergic activity
(68), free fatty acids, growth hormone, androgens, and PPARγ agonists, as reviewed in
detail elsewhere (69).
The discovery of leptin not only led to the realization that leptin per se plays a pivotal
role in the regulation of energy homeostasis but also opened the black box of energy
homeostasis regulation. Leptin is thought to act as a lipostat: as the amount of fat stored
in adipocytes rises, leptin is released into the blood and signals to the brain information
on adequacy of energy stores. Recent studies in mice underline the important role of
leptin in the development of hypothalamic circuits regulating energy homeostasis (70)
since leptin may affect the synaptic plasticity of hypothalamic neurons (71) and may
also act as a neurotrophic factor during hypothalamic development (72).
48 Kelesidis, Kelesidis, and Mantzoros
Although the role of leptin appears to be of significance in both ends of the energy
homeostasis spectrum, i.e., obesity and energy-deficient states (73), our work has dem-
onstrated that in humans leptin’s role appears to be of much more important in states of
energy deprivation (74–76). Our group has also recently shown that falling leptin levels
below a certain threshold can result in several neuroendocrine changes and immune
abnormalities that occur with starvation (75,77) whereas no alterations of these neu-
roendocrine axes and immune response occur when leptin fluctuates within the normal
range (78). Importantly, extremely thin women with hypothalamic amenorrhea and/
or anorexia nervosa have low leptin levels (79,80), whereas exogenous leptin normal-
izes neuroendocrine and reproductive function in women with relative hypoleptinemia
(76). The role of leptin in human obesity is intriguing. In rodents diet-induced obesity
has been correlated with the development of leptin resistance (81,82). Mutations in
ob gene (leptin gene), as well as the leptin receptor gene, result in morbid obesity and
diabetes in rodents and humans (62,83–85); however, these cases are extremely rare.
The majority of obese individuals are characterized by high levels of leptin (86), sug-
gesting leptin insensitivity or resistance; in fact, leptin administration to obese subjects
has only a moderate effect on body weight (87). Importantly, negative regulators of both
leptin and insulin signal transduction, such as inhibitors of protein tyrosine phosphatase
1B, may provide opportunities for the treatment of both obesity and insulin resistance
by improving these hormone resistance syndromes (69,88). Finally, the prospect that
leptin administration in replacement doses might prove clinically useful to maintain
weight loss and the resulting relative hypoleptinemia that has been achieved by more
traditional means (89,90) is an exciting possibility. Further testing of this concept in
humans is the focus of many research efforts. The complex role of leptin in regulation
of energy homeostasis and neuroendocrine function is summarized in Figs. 2 and 3a
and in Tables 2 and 3.
5.1.2. Adiponectin
Adiponectin, a 247-amino-acid protein produced exclusively by adipocytes, circu-
lates in trimers and higher order oligomers (91–94) (Figs. 3b and 4). Different adi-
ponectin isoforms, bind and activate at least two adiponectin receptors, which in turn
alter the phosphorylation state of 5¢-AMP kinase and possibly other downstream mol-
ecules (94,95). Adiponectin receptor 1 (AdipoR1), which is expressed ubiquitously,
but most abundantly in skeletal muscle, has a high affinity for globular adiponectin
and a very low affinity for full-length adiponectin, whereas adiponectin receptor 2
(AdipoR2), which is found predominantly in the liver, has an intermediate affinity for
both forms (96).
Adiponectin is currently considered to regulate not only insulin resistance but also
possibly energy homeostasis (91). It decreases with increasing overall and central adi-
posity (92,97–99), and increases with long-term weight reduction (100). Adiponectin
is increased after food restriction in rodents (101). Its levels are regulated in rodents
by ageing and high fat diet (102), and in humans by certain genetic polymorphisms
(103), Mediterranean diet (104), glycemic load (105), and exercise (106). Studies in
rodents have revealed that peripheral adiponectin administration reduces body weight
and visceral adiposity without affecting food intake (107,108), increases insulin sen-
sitivity, and decreases lipid levels in rodents (109–111). These effects are proposed to
occur mainly by regulating energy expenditure, increasing glucose uptake, free fatty
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 49
Food Intake
Energy Expenditure
Pituitary gland
+POMC α-MSH, etc
Hypophysis –NPY, AgRP, etc
+ – + +
+ + –
TSH FSH/ LH ACTH GH Leptin Insulin Immune Sympathetic
Function tone
–
+
Thyroid Estrogens Cortisol
Hormones Androgens
+ –
+/ –
Adipose tissue –
–
Fig. 2. Leptin’s role in energy homeostasis and neuroendocrine regulation. States of energy
excess are associated with increased leptin levels but both neuroendocrine function and energy
homeostasis are resistant to the effects of increased leptin. Energy deficiency results in decreasing
leptin levels and reduced leptin receptor activation in the arcuate nucleus of the hypothalamus.
This leads to activation of a complex neural circuitry comprising orexigenic and anorexigenic
signals. The main anorexigenic peptides are proopiomelanocortin and cocaine and amphetamine
regulated transcript; these are stimulated by leptin. The main orexigenic peptides downstream
of leptin are neuropeptide Y and agouti-related protein; both potently stimulate food intake and
reduce energy expenditure, thereby promoting weight gain in response to reducing leptin levels.
In the figure the response to anorexigenic stimuli (activated in states of energy excess) is shown.
“+” indicates stimulatory effects; “−” inhibitory effects. In states of energy deficiency the exact
reverse pathways are activated.
acid oxidation, and oxygen consumption in the periphery (95,108,109). This effect on
energy expenditure appears to be mediated by the hypothalamic melanocortin system
(111). Adiponectin knockout mice have severe diet-induced insulin resistance (112).
Importantly, accumulating evidence indicates that the primary role for adiponectin is to
regulate insulin sensitivity (96,110,113–115).
Circulating adiponectin levels correlate negatively with insulin resistance (98), and
low adiponectin levels predict increased risk for developing insulin resistance, diabetes,
cardiovascular disease and may represent a link between obesity and certain malignan-
cies (116). On the other hand, adiponectin levels are higher in states of improved insulin
sensitivity, such as after weight reduction or treatment with insulin-sensitizing drugs,
e.g. thiazolidinediones (94). In addition to its insulin-sensitizing effects, adiponectin can
decrease lipid levels (111) and has potent anti-inflammatory (117) and atheroprotective
effects (118–120). Although metabolic pathways that are involved in regulation of food
intake, gluconeogenesis, and lipogenesis (121) mediate some of the actions of adiponectin,
50 Kelesidis, Kelesidis, and Mantzoros
Table 2
Actions of Leptin That Can Regulate Energy Homeostasis and Metabolism by Organ and
System
Action of leptin Type of action of leptin
Energy intake Binding to and activation of leptin receptors found in hypotha-
lamic nuclei (mainly, but not exclusively, in arcuate and paraven-
tricular nucleus of the hypothalamus) and brainstem, triggers circuits
inhibiting appetite (mainly through upregulation of α-MSH
(POMC)) and inhibits circuits stimulating appetite (mainly by
suppressing neuropeptide Y and agouti-related peptide (AgRP)
expression in hypothalamic nuclei) (300).
Energy expenditure Experimental evidence points to both acute and chronic effects
of leptin to increase energy expenditure, both via activation
of BAT and increases in SNS firing per se (301,302). Acute
effects of leptin include increased catecholamine turnover in
BAT (301), increased SNS firing in numerous thermogenic
tissues (302), and lipolysis (303). The acute effects of leptin
may be important for body weight regulation because leptin
may prevent the decrease in energy expenditure that normally
accompanies decreased food intake in mice (304) and humans
(89). Leptin administration has not been shown to alter SNS
activity in healthy humans in the short term (305) but may alter
SNS activity in long-term weight-loss-induced hypoleptinemia
in humans (89). In any case, leptin’s effect on energy expendi-
ture in both weight-loss-induced and congenital hypoleptinemia
appears to be relatively small (85).
Autonomic nervous Activation of leptin receptors in the ventromedial hypothalamus
system axis and arcuate nucleus results in modulation of autonomic nervous
system activity. Acute leptin injections (i.v., intracerebroventricu-
lar – ICV, or intrahypothalamic into the VMH) increase sympa-
thetic nerve activity in mice (306–308). Through activation of
sympathetic nerves, leptin stimulates free fatty acid oxidation
and thermogenesis in brown adipose tissue in rodents (309). No
similar effects have been demonstrated to date in humans (305).
Peripheral tissues Leptin increases glucose uptake in several tissues, including
muscle and brown adipose tissue, and thus seems to play a role
in modulating peripheral insulin sensitivity (310). The latter is
likely to also involve activation of central melanocortin neurons
but more research is needed for underlying mechanisms to be
fully elucidated. Leptin administration has been shown to im-
prove insulin resistance in humans with congenital (311) or rela-
tive acquired leptin deficiency (310). Other important actions of
leptin include regulation of immune function, hematopoiesis in
mice (312) and humans (313,314), angiogenesis (73) and finally
bone metabolism (73).
BAT brown adipose tissue, MSH a-melanocyte-stimulating hormone, POMC proopiomelanocortin,
SNS sympathetic nervous system
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 51
Table 3
The Role of Leptin in Energy Homeostasis
The role of leptin in states of energy excess
• Children with leptin deficiency due to a leptin or leptin receptor (85) gene mutation are
normal at birth but develop morbid obesity in early childhood, which is responsive to leptin
treatment (315–317). Although monogenic obesity syndromes due to mutations in the leptin
or leptin receptor genes remain an uncommon cause of obesity, their existence underlines
the importance of the leptin system in the control of energy homeostasis in humans.
• Most obese humans and almost all mouse models of obesity (except ob/ob) have elevated lev-
els of leptin in serum (318). Administration of leptin to diet-induced obese mice, a model of
human obesity, resulted in only minimal weight loss (304), demonstrating that these hyperlep-
tinemic mice are leptin-resistant, probably because of receptor or postreceptor defects (318).
• Common human obesity is a leptin-resistant state with high circulating levels of leptin in
obese subjects and relative tolerance or deficiency in the actions of leptin (86,317,318).
• Although defective leptin transport through the blood–brain barrier to the hypothala-
mus, induction of leptin signaling inhibitors, or intracellular signaling defects in leptin-
responsive hypothalamic neurons have been designated as potential defects accountable
for leptin resistance (319–321), the exact mechanism of leptin tolerance or resistance to
its actions remains to be elucidated in humans.
• In view of the fact that leptin treatment depletes body fat specifically (304) the notion of lep-
tin tolerance or resistance to its actions was supported by clinical trials in which only modest
weight loss occurred in response to recombinant leptin (r-metHuLeptin) administration (87).
• Although rare patients with partial leptin deficiency may respond to exogenous leptin
treatment (322), larger, prospective, double-blinded and placebo-controlled clinical
trials in obese patients have shown only modest, dose-dependent weight loss in obese
patients, along with a high degree of variability in response (87).
• A possible role for falling leptin levels in the plateau phenomenon and the return to
baseline body weight in response to weight loss has been raised in a recent small and
uncontrolled study where leptin administration to maintain levels equal to those prior to
weight loss reversed changes observed with weight loss (89).
The role of leptin in states of energy deficiency
• Accumulating evidence suggests that leptin is physiologically more important as a signal
of energy deficiency than as a signal of energy excess.
• In contrast to the observation that leptin levels increase gradually over time as fat mass increas-
es, leptin levels are very sensitive to acute energy deprivation (77) and fall rapidly in response
to complete fasting, before and/or out of proportion to changes in fat mass (77,323,324).
• Starvation also elicits physiological adaptations of several neuroendocrine axes that
can be considered protective, from a teleological point of view, since they may divert
energy away from processes that are not essential for immediate survival during acute
starvation. We have shown that several neuroendocrine changes that occur with starva-
tion are the result of falling leptin levels in mice (67) and in humans (67,77).
• Exogenous leptin administration to normalize falling leptin levels in response to starva-
tion restores neuroendocrine function in normal men (77), but has only minimal effect
when leptin fluctuates within the normal range (75).
• Extremely thin women with hypothalamic amenorrhea and/or anorexia nervosa have
low leptin levels (79,80,325,326). Leptin treatment of strenuously exercising women
normalizes neuroendocrine and reproductive functions, as well as bone formation
markers in women with relative hypoleptinemia (76).
52 Kelesidis, Kelesidis, and Mantzoros
a Leptin b Adiponectin
Fig. 3. Tertiary structure of leptin (a) and adiponectin (b).
a
Non-homologous Collagen-like
Region Domain Globular Domain
28 93 230
b c
HMW
MMW (Hexamer)
LMW (Trimer)
Fig. 4. (a) Primary structure of adiponectin. (b) Multimeric structure of adiponectin. (c) Mul-
timers of adiponectin in an SDS gel (Western blot). HMW high molecular weight, MMW middle
molecular weight, LMW low molecular weight adiponectin.
the mechanism by which this adipokine improves insulin resistance, glucose metabolism,
and attenuation of weight gain remains to be fully elucidated. Further studies are needed
to fully elucidate the role of adiponectin in regulation of energy homeostasis.
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 53
5.1.3. Interleukin-6 and Interleukin-1
IL-6 is a multifunctional immune-modulating cytokine that circulates at high levels in
the blood stream. It has been suggested to have important functions in glucose and lipid
metabolism. IL-6 is secreted from adipose tissue into the circulation, and its expression is
positively correlated with BMI and total fat tissue mass. IL-6-knockout mice develop obes-
ity, which can partly be reversed by IL-6 replacement, suggesting a role for IL-6 in the long-
term regulation of adipose tissue mass (122). Furthermore, central administration of a low
dose of IL-6 decreases feeding and increases energy expenditure in rats, suggesting a central
site of action for IL-6 (122). Importantly, obesity can be associated with relative deficiency
of IL-6 centrally, since IL-6 levels in the CNS correlate inversely with subcutaneous and
total body fat in overweight and obese humans (123). Serum levels and tissue expression of
IL-6 decrease in response to diet-induced weight loss and increase with increasing adiposity
(124). Increased production of IL-6 by the adipose tissue, especially visceral adipose tis-
sue (125), of obese subjects may represent a compensatory mechanism attempting to limit
obesity. Plasma concentrations of IL-6 can predict the development of type 2 diabetes and
cardiovascular disease (61) since increased IL-6 levels result in a proinflammatory state, as
well as insulin signaling defects and thus insulin resistance (125,126).
Other interleukins, including IL-18 and IL-1, are also involved in body-weight
homeostasis. IL-1 type I receptor knockout mice display an obese and insulin-resistant
phenotype. This obese phenotype is characterised by a decrease in leptin sensitivity, fat
utilization, and locomotor activity (127). The emerging role of interleukins in energy
homeostasis and insulin resistance has been recently reviewed extensively elsewhere.
5.1.4. Resistin
Resistin, a recently identified 114-amino-acid protein, is almost exclusively expressed
in white-adipose tissue. Its concentrations have been reported to be higher in insulin-
resistant states as well as in visceral vs. subcutaneous adipose tissue (128). Circulating
resistin is increased in obese rodents (128) and humans (129) and falls after weight loss
in humans (130). Whether resistin influences obesity or insulin resistance either directly
or by altering glucose and insulin levels and/or whether resistin may play a direct or
indirect role in inflammation associated with obesity (131) warrants further investiga-
tion. Studies have shown contradictory results (128,132–139). Further studies are clearly
needed to elucidate the role of resistin in regulation of energy homeostasis (140).
5.1.5. Apelin
Apelin, a hormone with considerable sequence similarity with the angiotensin receptor
type 1 (AT-1) gene, was discovered many years ago (141) but its production in adipose
tissue and its potential modulating effect on obesity were recognized only very recently
(142). Apelin, similar to leptin and insulin, is an adipocyte-generated signal circulating in
proportion to body fat stores that may be acting to reduce food intake. In addition, simi-
lar to leptin, upregulation of apelin gene expression has been observed in certain mouse
models of obesity while insulin regulates apelin expression in adipose tissue (142,143).
Thus except for the previously described beneficial effects of apelin on cardiovascular
physiology and insulin sensitivity (143), apelin may also play a protective role in obesity-
associated disease states. However, more experimental evidence on the proposed roles of
apelin is needed since available data remain controversial (142,144–146).
54 Kelesidis, Kelesidis, and Mantzoros
5.1.6. Visfatin
Pre-B-cell colony-enhancing factor, a growth factor for early B lymphocytes
previously known to be synthesized in bone marrow, liver, and skeletal muscle,
was recently found to be highly expressed in human visceral fat (147,148) and was
referred to as “visfatin” since plasma visfatin concentration was found to correlate
strongly with the amount of visceral fat (147). Plasma visfatin levels were found to
be almost twofold higher in mice made obese by a high-fat diet in comparison
to lean animals (147). In humans, plasma visfatin has also been reported to correlate
significantly with visfatin mRNA level in visceral adipose tissue, percent body fat,
and body mass index (148). Experimental data also suggest that endogenous visfatin
is involved in the regulation of glucose homeostasis (147) and plasma visfatin levels
are also higher in patients with type 2 diabetes mellitus than in normoglycemic
controls (149,150), although this has not been confirmed by all studies (151). Future
studies are needed to clearly establish the exact role of visfatin in the development
of obesity and diabetes.
5.1.7. Other Hormones Produced by Adipose Tissue
Adipocytes produce other cytokines also, including tumor necrosis factor alpha (152)
and proteins such as macrophages and monocyte chemoatractant protein 1, plasminogen
activator inhibitor 1, and acylation stimulating protein (ASP), all of which have also been
studied in the context of regulation of obesity, metabolism, and the insulin resistance syn-
drome (61). These and other adipocyte-secreted molecules (see Table 1) are the focus of
intensive research efforts and their study is expected to contribute significantly to our under-
standing of the mechanisms regulating nutrition, metabolism, and energy homeostasis.
5.2. Pancreas/Pancreatic Hormones
5.2.1. Insulin
Insulin, a 51-amino-acid hormone, appears to be one of the most important hormones
regulating energy homeostasis. It is secreted from pancreatic beta cells and acts by binding
to and activating a glycoprotein insulin receptor expressed on the plasma membrane of
almost all cells. Subsequent tyrosine phosphorylation of the insulin receptor and initia-
tion of intracellular signaling lead to regulation of key cellular activities, including gene
expression, glucose uptake and oxidation, and synthesis of glycogen, triglycerides, and
protein (153).
Key areas responsible for controlling food intake, such as the arcuate nucleus in the
hypothalamus, express insulin binding sites (154), and intracerebroventricular infusion
of insulin dramatically decreases food intake and body weight in animals (155). In
contrast, neuron-specific insulin receptor knockout mice demonstrate increased food
intake, body weight, and adiposity, suggesting that insulin, similar to leptin, plays a
key role in regulating energy balance (156,157). Animal models of diet-induced obes-
ity and leptin resistance are also characterized by insulin resistance and reduced insulin
transport into the brain and thus weight gain and increased food intake may be due
to decreased central insulin levels in addition to defective leptin transport and leptin
resistance (158). Although both the melanocortin and neuropeptide Y (NPY) systems are
important downstream mediators of insulin’s actions on food intake and body weight,
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 55
the pathways mediating insulin’s effects on food intake remain to be fully elucidated
(159–161).
In humans, insulin, similar to leptin, circulates in levels proportional to the degree of
adiposity (162) which may serve to overcome impaired insulin-mediated intracellular
signaling or to increase insulin levels centrally (153). Negative regulators of both leptin
and insulin signal transduction, such as inhibitors of protein tyrosine phosphatase 1B,
may provide opportunities for the treatment of both obesity and insulin resistance (88).
Several compounds are currently in preclinical development by several pharmaceutical
companies and are anticipated with great interest as potential new treatment options for
obesity and diabetes.
5.2.2. Pancreatic Polypeptide
Pancreatic polypeptide (PP) is primarily produced by cells of the islets of Langer-
hans (163). It may modulate expression of other gut hormones such as ghrelin (164)
and/or regulate other hypothalamic neuropeptides such as NPY and orexin (164) and
convey anorectic signals via brain stem pathways (165). Thus even though PP could be
unable to cross the blood–brain barrier, it is possible that it could still regulate appetite.
Although less data are available on the interaction between PP and other adipokines
such as leptin, it has been shown that PP administration in leptin-deficient ob/ob mice
decreases body weight (164). We did not find any leptin-induced alterations in PP levels
in a recent interventional study in humans (166).
Transgenic mice overexpressing PP are leaner than controls (167), and chronic pe-
ripheral administration of PP to mice reduces body weight (168). The actions of PP on
food intake seem to depend on the route of administration. In obese rodents, peripheral
PP administration decreases food intake, reduces energy expenditure and body weight,
and improves insulin resistance and dyslipidemia (164,169). In humans, PP may reduce
food intake in normal-weight human volunteers (170) and in patients with Prader–Willi
syndrome (171). In contrast to the peripheral actions of PP, central administration of PP
into the third ventricle increases food intake (172) but the mechanisms involved remain
to be fully elucidated. Plasma PP concentrations have been inversely associated with
adiposity and subjects with anorexia have elevated levels of this peptide (173,174), while
reduced levels of plasma PP (175,176) have been linked to hyperphagia and obesity
in obese subjects (177,178). However, other studies show no difference in plasma PP
concentrations in response to weight loss in obese subjects (179), or between lean and
obese subjects (180), with the exception of Prader–Willi syndrome. Although obser-
vational studies of PP levels in humans are conflicting (176,181), intravenous infusion
of PP in normal-weight subjects has been shown to reduce 24-h energy intake (170).
Longitudinal prospective evaluation of Pima Indians over 5 years indicate that PP’s
role in regulating energy balance may be complex, since higher fasting PP levels were
associated with greater risk of weight gain, but higher postprandial PP levels were
associated with decreased risk of weight gain (182). Thus, the efficacy of PP infusion
in obesity remains to be further studied.
5.2 3. Amylin
Amylin, produced by the beta cells of the pancreas, is secreted along with insulin in
response to food ingestion. Its best known functions are to reduce food intake and gastric
56 Kelesidis, Kelesidis, and Mantzoros
emptying, and to inhibit pancreatic glucagon secretion and pancreatic and gastric enzyme
secretion (183). Importantly, amylin is deficient in patients with type 1 diabetes, who are
also deficient in insulin (183). In rats, amylin decreases food intake, body weight, and fat
mass, while inhibition of amylin signaling has the opposite effect (184,185).
Finally, there is evidence that amylin functions as an adiposity signal controlling
body weight (183,186), but the magnitude of its effects appears to be relatively small.
Amylin may interact with other signals controlling energy homeostasis at the level of
the hypothalamus and probably elsewhere, enhances the action of other satiety signals
at the level of the hindbrain, and can lead to reduction of meal size (185,187,188). In
rats, amylin has a synergistic effect with leptin to induce weight loss (189), specifically
decreasing fat mass (190), and a recent clinical trial in humans involving administration
of amylin and leptin suggests a similar synergy (http://www.amylin.com). Using an
interventional study design in healthy normal-weight humans, we have recently dem-
onstrated that amylin levels are decreased during short-term complete fasting, but this
effect is not mediated by leptin; we have also shown that amylin levels are not altered
by chronic energy deficit or normalizing leptin levels for up to 3 months (166). Thus,
any potential synergistic effect of amylin and leptin to mediate weight loss is likely not
due to alterations of amylin levels by leptin, but may be related to central mechanisms
and/or synergies in enhancing intracellular signaling.
The synthetic amylin analog pramlintide is marketed for diabetes treatment, but its
administration for at least 16 weeks in humans also causes mild progressive weight loss
(191,192) and can induce weight loss in individuals with (193) and without diabetes (194).
More studies are needed to fully quantitate amylin’s weight reducing capacity, its potential
synergistic effects with other peptides, and to carefully study potential side effects.
5.3. Gastrointestinal Tract Hormones
The gastrointestinal tract is also an endocrine organ and an important source of pep-
tide hormones which regulate energy balance. Gastrointestinal hormones have been
proposed to contribute to short-term regulation of energy homeostasis in contrast to
adipose-tissue-secreted or pancreas-derived hormones which have been proposed to
provide long-term signals that regulate energy homeostasis,. Therefore, gut hormone
signaling systems represent important pharmaceutical targets for potential antiobesity
therapies that would have a short acting role. Of the several gastrointestinal-tract-gener-
ated molecules we will focus herein on those considered to be the most important, such
as ghrelin, peptide YY (PYY), glucagon-like peptide 1 (GLP-1) and oxyntomodulin,
cholecystokinin (CCK), and bombesin-like peptides.
5.3.1. Ghrelin
Ghrelin, a 28-amino-acid peptide, is mainly expressed in enterochromaffin cells of the
stomach fundus (195) but may also be expressed centrally in the hypothalamus (196).
Its action is thought to be mediated via the growth hormone secretagogue receptor (GHS-R)
type 1a expressed in numerous tissues, including hypothalamus, pituitary, liver, and the
gastrointestinal tract (195). Plasma ghrelin levels are regulated both by food intake and
by endogenous diurnal rhythms (197). In normal humans, ghrelin levels rise before meals
(197) and in response to diet-induced weight loss (198) whereas they fall acutely after
feeding. The rise in preprandial ghrelin correlates with hunger scores in human subjects
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 57
eating spontaneously (199). Interestingly, the levels of ghrelin are correlated with adiposity
in humans, with an inverse relationship between plasma ghrelin levels and BMI (200).
Obese human subjects show reduced levels of plasma ghrelin, which rise to normal after
diet-induced weight loss (198). Moreover, in obese individuals the postprandial regula-
tion of ghrelin seems to be altered, which may be related to continuous food intake and/
or obesity (201). Obese patients have also decreased ghrelin levels after gastric bypass
surgery, which may contribute to maintaining decreased weight after surgery (198).
Furthermore, recent data in humans have demonstrated an inverse correlation between
ghrelin and leptin, but we have shown no direct regulation of ghrelin by leptin administra-
tion over the short term (period of a few hours to a few days) (202). Peripheral and central
administration of ghrelin to rodents induces positive energy balance by decreasing feeding,
as well as fat mass, and reduces fat utilization (203,204). Ghrelin is unique because it is
the only known gut hormone stimulating food intake. Intravenous administration of ghrelin
to healthy volunteers increases food intake (205).
A potentially important application of ghrelin is that ghrelin antagonists could possibly
be developed as antiobesity drugs. It has been shown that GHS-R knockout mice are
resistant to diet-induced obesity (206,207) and favor fat as a metabolic substrate when
on a high-fat diet (208). In another study, ghrelin and GHS-R knockout mice were found
not to have profoundly altered food intake or body weight on a normal diet (209,210).
GHS-R antagonists may therefore have beneficial effects in obese humans on high-fat
diet, but more experiments are needed to establish this hypothesis.
Knockout models have also provided further evidence for the role of ghrelin in glucose
homeostasis. Diabetic ghrelin knockout mice show less dramatic hyperphagia than do
controls (211), and ablating ghrelin attenuates diabetes in the ob/ob mouse models of
obesity (212). Moreover, ghrelin administration has been demonstrated to increase food
intake in certain patient groups such as in cancer (213) and dialysis patients (214) and
thus reduced ghrelin levels may be responsible in part for the loss of appetite and weight
often observed in these patients (213,214). Whether ghrelin plays an important role in
regulating energy homeostasis in humans remains to be seen through future interven-
tional studies involving new ghrelin analogs and antagonists currently in development
by pharmaceutical companies.
5.3.2. Peptide YY
PYY, a 36-amino-acid peptide (215), is secreted from the L cells of the small and large
bowel (216). There are two main forms of PYY in the circulation: PYY1–36 and PYY3–
36 (217). PYY levels decrease with fasting and increase rapidly after a meal (218). PYY
inhibits food intake through a gut–hypothalamic pathway that involves inhibition of NPY
via Y2 receptors in the arcuate nucleus and the dorsal motor nucleus of the vagus nerve
(219). Peripheral administration of PYY delays gastric emptying and gastric secretion,
inhibits food intake, and reduces weight gain in animals and humans (220–225). How-
ever, centrally administered PYY increases food intake in rodents (226,227). In humans,
endogenous levels of PYY may be lower in obese subjects, and PYY reduces appetite
and food intake when administered to obese or normal-weight subjects, suggesting that
a relative PYY deficiency may contribute to the development of obesity (228). We have
shown in humans that PYY increases after meal ingestion and decreases after fasting in a
manner consistent with a meal-related signal of energy homeostasis but circulating levels
58 Kelesidis, Kelesidis, and Mantzoros
of this gut-secreted molecule are independent of regulation by leptin over the short term
(229).We have also recently found that PYY levels are higher in obese patients after gas-
tric bypass surgery, a fact that may contribute to the increased efficiency of this procedure
in decreasing body weight (230). In a short phase Ic trial of 37 obese participants a PYY
nasal spray yielded somewhat promising results causing 1.3 lb of weight loss in 6 days
whereas an injectable PYY analog (AC-162352) has been tested in phase I studies, with
limited success due to nausea (231). Ongoing clinical trials involving PYY administra-
tion are awaited with great anticipation to further elucidate the role of this peptide in the
treatment of obesity in humans.
5.3.3. Incretins: Glucagon-Like Peptides (GLP-1,2)
and Glucose-Dependent Insulinotropic Peptide
Incretins such as glucose-dependent insulinotropic polypeptide (GIP) and the glu-
cagon-like peptides (mostly GLP-1 but also GLP-2) are intestinal hormones that are
released in response to ingestion of nutrients, especially carbohydrate (232). They have
a number of important biological effects, which include release of insulin, inhibition of
postprandial glucagon release, maintenance of β-cell mass, delay of gastric emptying,
and inhibition of feeding which result in negative energy balance (232). These properties
allow them to be potentially suitable agents for the treatment of type 2 diabetes.
Exogenous GLP-1 (central or peripheral administration) has been found to reduce
food and caloric intake (233,234), and to decrease weight gain (235), body weight,
and adiposity in rodents, whereas immunoblockade of central GLP-1 with antibodies
results in increased energy intake (236,237). Moreover, mice deficient in dipeptidyl
peptidase IV (DPP-IV), an inhibitor of GLP-1 degradation, are resistant to diet-induced
obesity and insulin resistance. Regardless of the anorectic actions of GLP-1 reported
in rodents, GLP-1 receptor knockout mice have normal feeding behavior (238,239).
The anorectic effect of GLP-1 is also present in humans (240,241). Preprandial subcu-
taneous GLP-1 injections reduce caloric intake by 15% and result in 0.5 kg of weight
loss over 5 days in obese individuals (242). Therefore, low circulating GLP-1 could
likely contribute to the pathogenesis and maintenance of obesity, and GLP-1 replace-
ment could restore satiety. The actions of both GLP-1 on feeding may be mediated
via the GLP-1 receptor, which is expressed in the hypothalamus, brainstem, and pe-
riphery (243). Although GLP-1 is presumed to produce its anorectic effect by acting
centrally, the exact mechanism of its action and its potential efficacy in humans need
to be further studied (232).
The role of GLP-2 has not been fully established; however, central administration
reduces feeding, probably via GLP-1 receptor (244). No effect of GLP-2 on feeding has
been reported in man (245).
GIP, a peptide secreted by the duodenum upon absorption of fat or glucose, is a potent
insulin secretagogue (246). It has been suggested that GIP may be implicated in a
peripheral decrease of energy expenditure and fat oxidation and is oversecreted in the
diet-induced mouse model of obesity. GIP receptor knockout mice are protected from
obesity and insulin resistance (246), but the role of GIP in humans is currently thought
to be less important than that of GLP-1.
In clinical trials, incretin mimetics and GLP-1 agonists such as exenatide and liraglutide
reduced fasting and postprandial glucose concentrations, with improvements in HbA1c
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 59
and modest weight loss when added to existing metformin and/or sulfonylurea therapy
in patients with type 2 diabetes (247–250). The modest weight loss caused by incretin
mimetics underlines the important role of incretins in regulation of body weight and
energy homeostasis. However, side effects, including nausea and vomiting, limit the
development of stronger, more efficacious, incretins that could lead to new potential
medications for treatment of obesity. Another important category of agents that target
the incretin axis include DPP-IV inhibitors, which act by suppressing the degradation
of a variety of bioactive peptides, including GLP-1, thereby extending their duration
of action (251). Sitagliptin was recently approved for the treatment of type 2 diabetes
whereas vildagliptin is furthest along in late-stage clinical development among other
DPP-IV inhibitors (251,252). Significant improvement of glycemic control in patients
with type 2 diabetes has been observed with sitagliptin (253–256) and vildagliptin
(257–259) treatment in several clinical trials. Long-term clinical studies are needed to
determine the benefits of targeting the incretin axis (alone or in combination with other
medications) for the treatment of type 2 diabetes.
5.3.4. Oxyntomodulin
Oxyntomodulin (OXM) is released from the small intestine in proportion to caloric
intake (260). Both central and peripheral OXM administration acutely reduces food
intake in rodents (261,262), and repeated administration reduces body weight gain and
adiposity (262) possibly through an effect on the thyroid axis and via increased energy
expenditure (262). Studies in humans (263) have shown that OXM reduces hunger and
food intake (263,264) and may also result in increased energy expenditure (265). Long-
term trials are needed to establish OXM as an antiobesity drug and whether it may be the
first therapy to suppress appetite and to concurrently increase spontaneous activity.
5.3.5. Cholecystokinin
CCK is a peptide that is released by the duodenum and jejunum in response to nutrient
ingestion (protein and fatty acid) (266), and by acting via specific receptors, it slows gastric
emptying and stimulates gastric distension, intestinal motility, gall bladder contraction,
and pancreatic enzyme secretion (267,268). Antagonists of these receptors increase food
and energy intake in rodents (269) and in human subjects (270).
Although peripheral administration of CCK reduces food intake acutely in animals and
humans (267), it may also lead to a compensatory increase in daily meal number and thus
results in little weight loss. Thus, despite its anorectic actions, repeated administration
of CCK does not influence body weight, and CCK is mostly involved in the short-term
control of food intake (271). Chronic administration of CCK antagonists or anti-CCK
antibodies increases weight gain in rodents, but without a significant change in food
intake (272,273). The long-term effect of CCK on body weight may be the result of
interaction with other signals of adiposity such as leptin, which enhances the satiating
effect of CCK (274). The evidence for a role of CCK in long-term body weight regulation,
and hence as a potential therapy for obesity, remains to be fully elucidated.
5.3.6. Bombesin-like Peptides
Bombesin and bombesin-like peptides such as gastrin-releasing peptide and neuro-
medin B are released from the gastrointestinal tract in response to food intake. These
peptides result in decreased food intake (275) and duration of feeding (276,277) and act
60 Kelesidis, Kelesidis, and Mantzoros
through specific G-protein-coupled receptors (278) which are widely expressed both in
the gastrointestinal tract and centrally (275,279) and signal to the brain information on
energy intake. Peripheral or central injections of bombesin reduce food intake (280,281)
independently of CCK in rodents (282). Bombesin receptor 3 (BRS-3) knockout mice
display hyperphagia, mild obesity, diabetes, and hypertension (283) New compounds
targeting this pathway are currently under preclinical development and are expected to
soon shed light on the role of these molecules in humans.
5.3.7. Apo A-IV
Apolipoprotein (apo) A-IV is a circulating glycoprotein secreted by the small intestine
in humans. It has been considered a key peptide involved in the processing of ingested
fat by the body (284). One site of action of the anorexic effect of apo A-IV appears to be
within the brain since apo A-IV is synthesized in the ventrobasal hypothalamus (285), a
general area in which other important feeding-related neuropeptides are also produced,
and hypothalamic apo A-IV mRNA levels fluctuate with metabolic state as well as with
time of day (286–288). Apo A-IV is also present in the cerebrospinal fluid, and its
cerebrospinal levels increase when fat is absorbed (289). Moreover, administration of
exogenous apo A-IV in the third ventricle reduces food intake (290). Because both intestinal
and hypothalamic apo A-IV are regulated by absorption of lipids, but not carbohydrates,
this peptide may be an important link between short- and long-term regulation of body
fat (286–288). A possible signaling role of apo A-IV in energy homeostasis is suggested
by the fact that systemic administration of exogenous apo A-IV decreases dose depend-
ently food intake of rats (286–289) and that administration of apo A-IV antiserum
increases food intake and body weight (290). All of these findings suggest that apo A-IV
likely interacts with other signals involved in the regulation of energy homeostasis, but
more studies are clearly needed to fully elucidate its role.
5.3.8. Enterostatin
Enterostatin is the aminoterminal pentapeptide of procolipase and is released from
pancreatic procolipase by proteolytic activity in the small intestine after the ingestion of
dietary fat (291). Enterostatin is expressed in both the gastrointestinal tract and the CNS
since both procolipase and enterostatin have been localized to the gastric mucosa and to
certain brain regions (amygdala, hypothalamus, cortex) (292). Enterostatin when admin-
istrated centrally or peripherally to overnight fasted rats induces satiation since it sup-
presses intake of a high-fat diet, but not a high-carbohydrate diet (293,294). Finally, a
role for endogenously produced enterostatin in feeding behavior is suggested by its abil-
ity to increase intake of high-fat diets by the enterostatin antagonist β-casomorphin1–7
(295). Further studies are needed to fully elucidate the role of this peptide in regulation
of food intake and energy homeostasis.
5.3.9. Obestatin
It has recently been reported that obestatin, a new peptide derived from the ghrelin
gene, inhibits food intake by acting through the orphan receptor GPR39 (296,297).
Despite this evidence there are some discrepancies in relation to the anorectic effect
of obestatin (298) as well as its binding to GPR39 (299). If the anorectic effect is con-
firmed, this finding could provide a new drug target for the treatment of obesity.
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 61
6. CONCLUSION
In summary, regulation of energy homeostasis is extremely complex. Signals from
the environment and the periphery are integrated by the CNS to regulate both energy
intake and energy expenditure. As the secrets of the systems responsible for the energy
homeostasis regulation continue to be decoded, promising prospects emerge for the
development of novel antiobesity medications which should produce more substantial
weight loss than is currently achieved with nonsurgical interventions. This will hope-
fully provide in the not so distant future substantial benefits to the increasing percentage
of the population striving to control their body weight.
REFERENCES
1. Akabayashi A, Zaia CT, Silva I, Chae HJ, Leibowitz SF. Neuropeptide Y in the arcuate nucleus is
modulated by alterations in glucose utilization. Brain Res 1993; 621(2):343–348.
2. Muroya S, Yada T, Shioda S, Takigawa M. Glucose-sensitive neurons in the rat arcuate nucleus contain
neuropeptide Y. Neurosci Lett 1999; 264(1–3):113–116.
3. Lynch RM, Tompkins LS, Brooks HL, Dunn-Meynell AA, Levin BE. Localization of glucokinase gene
expression in the rat brain. Diabetes 2000; 49(5):693–700.
4. Burdyga G, Spiller D, Morris R, Lal S, Thompson DG, Saeed S et al. Expression of the leptin receptor
in rat and human nodose ganglion neurones. Neuroscience 2002; 109(2):339–347.
5. Moriarty P, Dimaline R, Thompson DG, Dockray GJ. Characterization of cholecystokininA and chole-
cystokininB receptors expressed by vagal afferent neurons. Neuroscience 1997; 79(3):905–913.
6. Peters JC, Wyatt HR, Donahoo WT, Hill JO. From instinct to intellect: the challenge of maintaining
healthy weight in the modern world. Obes Rev 2002; 3(2):69–74.
7. Brownell K. Public policy and the prevention of obesity. In: Fairburn CG, Brownell K, editors. Eating
disorders and obesity. New York: The Guilford, 2001: 619–624.
8. Hill JO, Peters JC. Environmental contributions to the obesity epidemic. Science 1998;
280(5368):1371–1374.
9. Hill JO, Wyatt HR, Reed GW, Peters JC. Obesity and the environment: where do we go from here.
Science 2003; 299(5608):853–855.
10. Boutin P, Froguel P. Genetics of human obesity. Best Pract Res Clin Endocrinol Metab 2001;
15(3):391–404.
11. Hill J, Pagliassotti M, Peters J. Nongenetic determinants of obesity and fat topography. In: Bouchard C,
editor. Genetic determinants of obesity. Boca Raton, FL: CRC, 1994: 35–48.
12. Lingford-Hughes A, Nutt D. Neurobiology of addiction and implications for treatment. Br J Psychiatry
2003; 182:97–100.
13. Rogers PJ, Smit HJ. Food craving and food “addiction”: a critical review of the evidence from a biopsy-
chosocial perspective. Pharmacol Biochem Behav 2000; 66(1):3–14.
14. Gulati K, Ray A, Sharma KK. Role of diurnal variation and receptor specificity in the opioidergic regu-
lation of food intake in free-fed and food-deprived rats. Physiol Behav 1991; 49(6):1065–1071.
15. Triscari J, Nelson D, Vincent GP, Li CH. Effect of centrally and peripherally administered beta-
endorphin on food intake in rats. Int J Pept Protein Res 1989; 34(5):358–362.
16. Berridge KC, Robinson TE. Parsing reward. Trends Neurosci 2003; 26(9):507–513.
17. Mogenson GJ, Jones DL, Yim CY. From motivation to action: functional interface between the limbic
system and the motor system. Prog Neurobiol 1980; 14(2–3):69–97.
18. Zahm DS. An integrative neuroanatomical perspective on some subcortical substrates of adaptive
responding with emphasis on the nucleus accumbens. Neurosci Biobehav Rev 2000; 24(1):85–105.
19. Otake K, Nakamura Y. Possible pathways through which neurons of the shell of the nucleus accumbens
influence the outflow of the core of the nucleus accumbens. Brain Dev 2000; 22(Suppl 1):S17–S26.
20. Usuda I, Tanaka K, Chiba T. Efferent projections of the nucleus accumbens in the rat with special refer-
ence to subdivision of the nucleus: biotinylated dextran amine study. Brain Res 1998; 797(1):73–93.
62 Kelesidis, Kelesidis, and Mantzoros
21. Berthoud HR. Homeostatic and non-homeostatic pathways involved in the control of food intake and
energy balance. Obesity (Silver Spring) 2006; 14(Suppl 5):197S–200S.
22. Yeomans MR. Palatability and the micro-structure of feeding in humans: the appetizer effect. Appetite
1996; 27(2):119–133.
23. Drewnowski A, Greenwood MR. Cream and sugar: human preferences for high-fat foods. Physiol
Behav 1983; 30(4):629–633.
24. Lyman B. The nutritional values and food group characteristics of foods preferred during various
emotions. J Psychol 1982; 112(1st Half):121–127.
25. Taylor GJ, Parker JD, Bagby RM, Bourke MP. Relationships between alexithymia and psychological
characteristics associated with eating disorders. J Psychosom Res 1996; 41(6):561–568.
26. Parker G, Parker I, Brotchie H. Mood state effects of chocolate. J Affect Disord 2006; 92(2–3):149–159.
27. Heatherton TF, Herman CP, Polivy J. Effects of distress on eating: the importance of ego-involvement.
J Pers Soc Psychol 1992; 62(5):801–803.
28. Obici S, Rossetti L. Minireview: nutrient sensing and the regulation of insulin action and energy
balance. Endocrinology 2003; 144(12):5172–5178.
29. Campfield LA, Smith FJ, Burn P. The OB protein (leptin) pathway – a link between adipose tissue mass
and central neural networks. Horm Metab Res 1996; 28(12):619–632.
30. Patti ME, Kahn BB. Nutrient sensor links obesity with diabetes risk. Nat Med 2004; 10(10):1049–1050.
31. Loftus TM, Jaworsky DE, Frehywot GL, Townsend CA, Ronnett GV, Lane MD et al. Reduced
food intake and body weight in mice treated with fatty acid synthase inhibitors. Science 2000;
288(5475):2379–2381.
32. Makimura H, Mizuno TM, Yang XJ, Silverstein J, Beasley J, Mobbs CV. Cerulenin mimics effects of
leptin on metabolic rate, food intake, and body weight independent of the melanocortin system, but
unlike leptin, cerulenin fails to block neuroendocrine effects of fasting. Diabetes 2001; 50(4):733–739.
33. Kumar MV, Shimokawa T, Nagy TR, Lane MD. Differential effects of a centrally acting fatty acid
synthase inhibitor in lean and obese mice. Proc Natl Acad Sci USA 2002; 99(4):1921–1925.
34. Mobbs CV, Makimura H. Block the FAS, lose the fat. Nat Med 2002; 8(4):335–336.
35. Shimokawa T, Kumar MV, Lane MD. Effect of a fatty acid synthase inhibitor on food intake and
expression of hypothalamic neuropeptides. Proc Natl Acad Sci USA 2002; 99(1):66–71.
36. Thupari JN, Landree LE, Ronnett GV, Kuhajda FP. C75 increases peripheral energy utilization and fatty
acid oxidation in diet-induced obesity. Proc Natl Acad Sci USA 2002; 99(14):9498–9502.
37. Tu Y, Thupari JN, Kim EK, Pinn ML, Moran TH, Ronnett GV et al. C75 alters central and periph-
eral gene expression to reduce food intake and increase energy expenditure. Endocrinology 2005;
146(1):486–493.
38. Clegg DJ, Benoit SC, Air EL, Jackman A, Tso P, D’Alessio D et al. Increased dietary fat atten-
uates the anorexic effects of intracerebroventricular injections of MTII. Endocrinology 2003;
144(7):2941–2946.
39. Ronnett GV, Kleman AM, Kim EK, Landree LE, Tu Y. Fatty acid metabolism, the central nervous
system, and feeding. Obesity (Silver Spring) 2006; 14(Suppl 5):201S–207S.
40. Kim EK, Miller I, Landree LE, Borisy-Rudin FF, Brown P, Tihan T et al. Expression of FAS within
hypothalamic neurons: a model for decreased food intake after C75 treatment. Am J Physiol Endocrinol
Metab 2002; 283(5):E867–E879.
41. Kim EK, Miller I, Aja S, Landree LE, Pinn M, McFadden J et al. C75, a fatty acid synthase inhibitor,
reduces food intake via hypothalamic AMP-activated protein kinase. J Biol Chem 2004; 279(19):19970–
19976.
42. Landree LE, Hanlon AL, Strong DW, Rumbaugh G, Miller IM, Thupari JN et al. C75, a fatty acid
synthase inhibitor, modulates AMP-activated protein kinase to alter neuronal energy metabolism.
J Biol Chem 2004; 279(5):3817–3827.
43. Willett WC. Dietary fat plays a major role in obesity: no. Obes Rev 2002; 3(2):59–68.
44. Astrup A. Dietary composition, substrate balances and body fat in subjects with a predisposition to
obesity. Int J Obes Relat Metab Disord 1993; 17(Suppl 3):S32–S36.
45. McDevitt RM, Poppitt SD, Murgatroyd PR, Prentice AM. Macronutrient disposal during controlled
overfeeding with glucose, fructose, sucrose, or fat in lean and obese women. Am J Clin Nutr 2000;
72(2):369–377.
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 63
46. Flatt J. Energetics of intermediary metabolism. In: Garrow JS, Halliday D, editors. Substrate and energy
metabolism in man. London: John Libbey, 1985: 58–69.
47. Malik VS, Hu FB. Popular weight-loss diets: from evidence to practice. Nat Clin Pract Cardiovasc Med
2007; 4(1):34–41.
48. Nordmann AJ, Nordmann A, Briel M, Keller U, Yancy WS, Jr, Brehm BJ et al. Effects of low-carbo-
hydrate vs low-fat diets on weight loss and cardiovascular risk factors: a meta-analysis of randomized
controlled trials. Arch Intern Med 2006; 166(3):285–293.
49. Halton TL, Hu FB. The effects of high protein diets on thermogenesis, satiety and weight loss: a critical
review. J Am Coll Nutr 2004; 23(5):373–385.
50. Feinman RD, Fine EJ. Thermodynamics and metabolic advantage of weight loss diets. Metab Syndr
Relat Disord 2003; 1:209–219.
51. Segal-Isaacson CJ, Johnson S, Tomuta V, Cowell B, Stein DT. A randomized trial comparing low-fat
and low-carbohydrate diets matched for energy and protein. Obes Res 2004; 12(Suppl 2):130S–140S.
52. Astrup A, Meinert LT, Harper A. Atkins and other low-carbohydrate diets: hoax or an effective tool for
weight loss. Lancet 2004; 364(9437):897–899.
53. Buchholz AC, Schoeller DA. Is a calorie a calorie. Am J Clin Nutr 2004; 79(5):899S–906S.
54. Brehm BJ, Seeley RJ, Daniels SR, D’Alessio DA. A randomized trial comparing a very low carbohy-
drate diet and a calorie-restricted low fat diet on body weight and cardiovascular risk factors in healthy
women. J Clin Endocrinol Metab 2003; 88(4):1617–1623.
55. Erlanson-Albertsson C, Mei J. The effect of low carbohydrate on energy metabolism. Int J Obes (Lond)
2005; 29(Suppl 2):S26–S30.
56. Adam-Perrot A, Clifton P, Brouns F. Low-carbohydrate diets: nutritional and physiological aspects.
Obes Rev 2006; 7(1):49–58.
57. Haymond MW, Karl IE, Clarke WL, Pagliara AS, Santiago JV. Differences in circulating gluconeogenic
substrates during short-term fasting in men, women, and children. Metabolism 1982; 31(1):33–42.
58. Denke MA. Metabolic effects of high-protein, low-carbohydrate diets. Am J Cardiol 2001; 88(1):59–61.
59. Schoeller DA, Buchholz AC. Energetics of obesity and weight control: does diet composition matter?
J Am Diet Assoc 2005; 105(5 Suppl 1):S24–S28.
60. Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish,
Weight Watchers, and Zone diets for weight loss and heart disease risk reduction: a randomized trial.
JAMA 2005; 293(1):43–53.
61. Kershaw EE, Flier JS. Adipose tissue as an endocrine organ. J Clin Endocrinol Metab 2004;
89(6):2548–2556.
62. Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM. Positional cloning of the mouse
obese gene and its human homologue. Nature 1994; 372(6505):425–432.
63. Moschos S, Chan JL, Mantzoros CS. Leptin and reproduction: a review. Fertil Steril 2002; 77(3):433–444.
64. Auwerx J, Staels B. Leptin. Lancet 1998; 351(9104):737–742.
65. Flier JS. Obesity wars: molecular progress confronts an expanding epidemic. Cell 2004; 116(2):337–350.
66. Mantzoros CS, Flier JS. Editorial: leptin as a therapeutic agent – trials and tribulations. J Clin Endocrinol
Metab 2000; 85(11):4000–4002.
67. Ahima RS, Prabakaran D, Mantzoros C, Qu D, Lowell B, Maratos-Flier E et al. Role of leptin in the
neuroendocrine response to fasting. Nature 1996; 382(6588):250–252.
68. Mantzoros CS, Qu D, Frederich RC, Susulic VS, Lowell BB, Maratos-Flier E et al. Activation of
beta(3) adrenergic receptors suppresses leptin expression and mediates a leptin-independent inhibition
of food intake in mice. Diabetes 1996; 45(7):909–914.
69. Brennan AM, Mantzoros CS. Drug insight: the role of leptin in human physiology and pathophysiology
– emerging clinical applications. Nat Clin Pract Endocrinol Metab 2006; 2(6):318–327.
70. Matochik JA, London ED, Yildiz BO, Ozata M, Caglayan S, DePaoli AM et al. Effect of leptin
replacement on brain structure in genetically leptin-deficient adults. J Clin Endocrinol Metab 2005;
90(5):2851–2854.
71. Pinto S, Roseberry AG, Liu H, Diano S, Shanabrough M, Cai X et al. Rapid rewiring of arcuate nucleus
feeding circuits by leptin. Science 2004; 304(5667):110–115.
72. Bouret SG, Draper SJ, Simerly RB. Trophic action of leptin on hypothalamic neurons that regulate
feeding. Science 2004; 304(5667):108–110.
64 Kelesidis, Kelesidis, and Mantzoros
73. Kelesidis T, Mantzoros CS. The emerging role of leptin in humans. Pediatr Endocrinol Rev 2006;
3(3):239–248.
74. Chan JL, Mantzoros CS. Role of leptin in energy-deprivation states: normal human physiol-
ogy and clinical implications for hypothalamic amenorrhoea and anorexia nervosa. Lancet 2005;
366(9479):74–85.
75. Chan JL, Matarese G, Shetty GK, Raciti P, Kelesidis I, Aufiero D et al. Differential regulation of
metabolic, neuroendocrine, and immune function by leptin in humans. Proc Natl Acad Sci USA 2006;
103(22):8481–8486.
76. Welt CK, Chan JL, Bullen J, Murphy R, Smith P, DePaoli AM et al. Recombinant human leptin in
women with hypothalamic amenorrhea. N Engl J Med 2004; 351(10):987–997.
77. Chan JL, Heist K, DePaoli AM, Veldhuis JD, Mantzoros CS. The role of falling leptin levels in the
neuroendocrine and metabolic adaptation to short-term starvation in healthy men. J Clin Invest 2003;
111(9):1409–1421.
78. Chan JL, Matarese G, Shetty GK, Raciti P, Kelesidis I, Aufiero D et al. Differential regulation of
metabolic, neuroendocrine, and immune function by leptin in humans. Proc Natl Acad Sci USA 2006;
103(22):8481–8486.
79. Miller KK, Parulekar MS, Schoenfeld E, Anderson E, Hubbard J, Klibanski A et al. Decreased leptin
levels in normal weight women with hypothalamic amenorrhea: the effects of body composition and
nutritional intake. J Clin Endocrinol Metab 1998; 83(7):2309–2312.
80. Laughlin GA, Yen SS. Hypoleptinemia in women athletes: absence of a diurnal rhythm with amenor-
rhea. J Clin Endocrinol Metab 1997; 82(1):318–321.
81. Van Heek M, Compton DS, France CF, Tedesco RP, Fawzi AB, Graziano MP et al. Diet-induced obese
mice develop peripheral, but not central, resistance to leptin. J Clin Invest 1997; 99(3):385–390.
82. Levin BE, Dunn-Meynell AA. Reduced central leptin sensitivity in rats with diet-induced obesity. Am
J Physiol Regul Integr Comp Physiol 2002; 283(4):R941–R948.
83. Coleman DL. Obese and diabetes: two mutant genes causing diabetes-obesity syndromes in mice. Dia-
betologia 1978; 14(3):141–148.
84. Friedman JM, Leibel RL. Tackling a weighty problem. Cell 1992; 69(2):217–220.
85. Farooqi IS, Wangensteen T, Collins S, Kimber W, Matarese G, Keogh JM et al. Clinical and molecular
genetic spectrum of congenital deficiency of the leptin receptor. N Engl J Med 2007; 356(3):237–247.
86. Considine RV, Sinha MK, Heiman ML, Kriauciunas A, Stephens TW, Nyce MR et al. Serum immunoreac-
tive-leptin concentrations in normal-weight and obese humans. N Engl J Med 1996; 334(5):292–295.
87. Heymsfield SB, Greenberg AS, Fujioka K, Dixon RM, Kushner R, Hunt T et al. Recombinant leptin
for weight loss in obese and lean adults: a randomized, controlled, dose-escalation trial. JAMA 1999;
282(16):1568–1575.
88. Dadke S, Chernoff J. Protein-tyrosine phosphatase 1B as a potential drug target for obesity. Curr Drug
Targets Immune Endocr Metabol Disord 2003; 3(4):299–304.
89. Rosenbaum M, Goldsmith R, Bloomfield D, Magnano A, Weimer L, Heymsfield S et al. Low-dose
leptin reverses skeletal muscle, autonomic, and neuroendocrine adaptations to maintenance of reduced
weight. J Clin Invest 2005; 115(12):3579–3586.
90. Boozer CN, Leibel RL, Love RJ, Cha MC, Aronne LJ. Synergy of sibutramine and low-dose leptin in
treatment of diet-induced obesity in rats. Metabolism 2001; 50(8):889–893.
91. Scherer PE, Williams S, Fogliano M, Baldini G, Lodish HF. A novel serum protein similar to C1q,
produced exclusively in adipocytes. J Biol Chem 1995; 270(45):26746–26749.
92. Arita Y, Kihara S, Ouchi N, Takahashi M, Maeda K, Miyagawa J et al. Paradoxical decrease of an adi-
pose-specific protein, adiponectin, in obesity. Biochem Biophys Res Commun 1999; 257(1):79–83.
93. Wang GJ, Volkow ND, Fowler JS. The role of dopamine in motivation for food in humans: implications
for obesity. Expert Opin Ther Targets 2002; 6(5):601–609.
94. Chandran M, Phillips SA, Ciaraldi T, Henry RR. Adiponectin: more than just another fat cell hormone?
Diabetes Care 2003; 26(8):2442–2450.
95. Yamauchi T, Kamon J, Ito Y, Tsuchida A, Yokomizo T, Kita S et al. Cloning of adiponectin receptors
that mediate antidiabetic metabolic effects. Nature 2003; 423(6941):762–769.
96. Kubota N, Terauchi Y, Yamauchi T, Kubota T, Moroi M, Matsui J et al. Disruption of adiponectin
causes insulin resistance and neointimal formation. J Biol Chem 2002; 277(29):25863–25866.
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 65
97. Hu E, Liang P, Spiegelman BM. AdipoQ is a novel adipose-specific gene dysregulated in obesity.
J Biol Chem 1996; 271(18):10697–10703.
98. Hotta K, Funahashi T, Bodkin NL, Ortmeyer HK, Arita Y, Hansen BC et al. Circulating concentra-
tions of the adipocyte protein adiponectin are decreased in parallel with reduced insulin sensitivity
during the progression to type 2 diabetes in rhesus monkeys. Diabetes 2001; 50(5):1126–1133.
99. Gavrila A, Chan JL, Yiannakouris N, Kontogianni M, Miller LC, Orlova C et al. Serum adiponectin
levels are inversely associated with overall and central fat distribution but are not directly regulated
by acute fasting or leptin administration in humans: cross-sectional and interventional studies. J Clin
Endocrinol Metab 2003; 88(10):4823–4831.
100. Yang WS, Lee WJ, Funahashi T, Tanaka S, Matsuzawa Y, Chao CL et al. Weight reduction increases
plasma levels of an adipose-derived anti-inflammatory protein, adiponectin. J Clin Endocrinol Metab
2001; 86(8):3815–3819.
101. Berg AH, Combs TP, Scherer PE. ACRP30/adiponectin: an adipokine regulating glucose and lipid
metabolism. Trends Endocrinol Metab 2002; 13(2):84–89.
102. Bullen JW, Jr, Bluher S, Kelesidis T, Mantzoros CS. Regulation of adiponectin and its receptors in
response to development of diet induced obesity in mice. Am J Physiol Endocrinol Metab 2007;
292(4):E1079–E1086.
103. Qi L, Doria A, Manson JE, Meigs JB, Hunter D, Mantzoros CS et al. Adiponectin genetic vari-
ability, plasma adiponectin, and cardiovascular risk in patients with type 2 diabetes. Diabetes 2006;
55(5):1512–1516.
104. Mantzoros CS, Williams CJ, Manson JE, Meigs JB, Hu FB. Adherence to the Mediterranean dietary
pattern is positively associated with plasma adiponectin concentrations in diabetic women. Am J Clin
Nutr 2006; 84(2):328–335.
105. Qi L, Rimm E, Liu S, Rifai N, Hu FB. Dietary glycemic index, glycemic load, cereal fiber, and plasma
adiponectin concentration in diabetic men. Diabetes Care 2005; 28(5):1022–1028.
106. Bluher M, Bullen JW, Jr, Lee JH, Kralisch S, Fasshauer M, Kloting N et al. Circulating adiponectin
and expression of adiponectin receptors in human skeletal muscle: associations with metabolic pa-
rameters and insulin resistance and regulation by physical training. J Clin Endocrinol Metab 2006;
91(6):2310–2316.
107. Masaki T, Chiba S, Yasuda T, Tsubone T, Kakuma T, Shimomura I et al. Peripheral, but not central,
administration of adiponectin reduces visceral adiposity and upregulates the expression of uncoupling
protein in agouti yellow (Ay/a) obese mice. Diabetes 2003; 52(9):2266–2273.
108. Fruebis J, Tsao TS, Javorschi S, Ebbets-Reed D, Erickson MR, Yen FT et al. Proteolytic cleavage
product of 30-kDa adipocyte complement-related protein increases fatty acid oxidation in muscle and
causes weight loss in mice. Proc Natl Acad Sci USA 2001; 98(4):2005–2010.
109. Berg AH, Combs TP, Du X, Brownlee M, Scherer PE. The adipocyte-secreted protein Acrp30 enhances
hepatic insulin action. Nat Med 2001; 7(8):947–953.
110. Yamauchi T, Kamon J, Waki H, Terauchi Y, Kubota N, Hara K et al. The fat-derived hormone
adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nat Med 2001;
7(8):941–946.
111. Qi Y, Takahashi N, Hileman SM, Patel HR, Berg AH, Pajvani UB et al. Adiponectin acts in the brain
to decrease body weight. Nat Med 2004; 10(5):524–529.
112. Maeda N, Shimomura I, Kishida K, Nishizawa H, Matsuda M, Nagaretani H et al. Diet-induced insulin
resistance in mice lacking adiponectin/ACRP30. Nat Med 2002; 8(7):731–737.
113. Bluher M, Michael MD, Peroni OD, Ueki K, Carter N, Kahn BB et al. Adipose tissue selective insulin receptor
knockout protects against obesity and obesity-related glucose intolerance. Dev Cell 2002; 3(1):25–38.
114. Stefan N, Vozarova B, Funahashi T, Matsuzawa Y, Weyer C, Lindsay RS et al. Plasma adiponectin
concentration is associated with skeletal muscle insulin receptor tyrosine phosphorylation, and low
plasma concentration precedes a decrease in whole-body insulin sensitivity in humans. Diabetes 2002;
51(6):1884–1888.
115. Lindsay RS, Funahashi T, Hanson RL, Matsuzawa Y, Tanaka S, Tataranni PA et al. Adiponectin and
development of type 2 diabetes in the Pima Indian population. Lancet 2002; 360(9326):57–58.
116. Kelesidis I, Kelesidis T, Mantzoros CS. Adiponectin and cancer: a systematic review. Br J Cancer
2006; 94(9):1221–1225.
66 Kelesidis, Kelesidis, and Mantzoros
117. Yokota T, Oritani K, Takahashi I, Ishikawa J, Matsuyama A, Ouchi N et al. Adiponectin, a new mem-
ber of the family of soluble defense collagens, negatively regulates the growth of myelomonocytic
progenitors and the functions of macrophages. Blood 2000; 96(5):1723–1732.
118. Ouchi N, Kihara S, Arita Y, Maeda K, Kuriyama H, Okamoto Y et al. Novel modulator for en-
dothelial adhesion molecules: adipocyte-derived plasma protein adiponectin. Circulation 1999;
100(25):2473–2476.
119. Ouchi N, Kihara S, Arita Y, Nishida M, Matsuyama A, Okamoto Y et al. Adipocyte-derived plasma
protein, adiponectin, suppresses lipid accumulation and class A scavenger receptor expression in hu-
man monocyte-derived macrophages. Circulation 2001; 103(8):1057–1063.
120. Mantzoros CS, Li T, Manson JE, Meigs JB, Hu FB. Circulating adiponectin levels are associated with
better glycemic control, more favorable lipid profile, and reduced inflammation in women with type
2 diabetes. J Clin Endocrinol Metab 2005; 90(8):4542–4548.
121. Shklyaev S, Aslanidi G, Tennant M, Prima V, Kohlbrenner E, Kroutov V et al. Sustained peripheral
expression of transgene adiponectin offsets the development of diet-induced obesity in rats. Proc Natl
Acad Sci USA 2003; 100(24):14217–14222.
122. Wallenius K, Wallenius V, Sunter D, Dickson SL, Jansson JO. Intracerebroventricular interleukin-6
treatment decreases body fat in rats. Biochem Biophys Res Commun 2002; 293(1):560–565.
123. Stenlof K, Wernstedt I, Fjallman T, Wallenius V, Wallenius K, Jansson JO. Interleukin-6 levels in the central
nervous system are negatively correlated with fat mass in overweight/obese subjects. J Clin Endocrinol
Metab 2003; 88(9):4379–4383.
124. Bastard JP, Jardel C, Bruckert E, Blondy P, Capeau J, Laville M et al. Elevated levels of interleukin
6 are reduced in serum and subcutaneous adipose tissue of obese women after weight loss. J Clin
Endocrinol Metab 2000; 85(9):3338–3342.
125. Fried SK, Bunkin DA, Greenberg AS. Omental and subcutaneous adipose tissues of obese subjects
release interleukin-6: depot difference and regulation by glucocorticoid. J Clin Endocrinol Metab
1998; 83(3):847–850.
126. Hotamisligil GS, Arner P, Caro JF, Atkinson RL, Spiegelman BM. Increased adipose tissue expres-
sion of tumor necrosis factor-alpha in human obesity and insulin resistance. J Clin Invest 1995;
95(5):2409–2415.
127. Garcia MC, Wernstedt I, Berndtsson A, Enge M, Bell M, Hultgren O et al. Mature-onset obesity in
interleukin-1 receptor I knockout mice. Diabetes 2006; 55(5):1205–1213.
128. Steppan CM, Bailey ST, Bhat S, Brown EJ, Banerjee RR, Wright CM et al. The hormone resistin links
obesity to diabetes. Nature 2001; 409(6818):307–312.
129. Savage DB, Sewter CP, Klenk ES, Segal DG, Vidal-Puig A, Considine RV et al. Resistin/Fizz3 expres-
sion in relation to obesity and peroxisome proliferator-activated receptor-gamma action in humans.
Diabetes 2001; 50(10):2199–2202.
130. Valsamakis G, McTernan PG, Chetty R, Al Daghri N, Field A, Hanif W et al. Modest weight loss
and reduction in waist circumference after medical treatment are associated with favorable changes
in serum adipocytokines. Metabolism 2004; 53(4):430–434.
131. Holcomb IN, Kabakoff RC, Chan B, Baker TW, Gurney A, Henzel W et al. FIZZ1, a novel cysteine-
rich secreted protein associated with pulmonary inflammation, defines a new gene family. EMBO J
2000; 19(15):4046–4055.
132. McTernan PG, Fisher FM, Valsamakis G, Chetty R, Harte A, McTernan CL et al. Resistin and type 2
diabetes: regulation of resistin expression by insulin and rosiglitazone and the effects of recombinant
resistin on lipid and glucose metabolism in human differentiated adipocytes. J Clin Endocrinol Metab
2003; 88(12):6098–6106.
133. Steppan CM, Lazar MA. Resistin and obesity-associated insulin resistance. Trends Endocrinol Metab
2002; 13(1):18–23.
134. Way JM, Gorgun CZ, Tong Q, Uysal KT, Brown KK, Harrington WW et al. Adipose tissue resistin
expression is severely suppressed in obesity and stimulated by peroxisome proliferator-activated
receptor gamma agonists. J Biol Chem 2001; 276(28):25651–25653.
135. Lee JH, Chan JL, Yiannakouris N, Kontogianni M, Estrada E, Seip R et al. Circulating resistin levels
are not associated with obesity or insulin resistance in humans and are not regulated by fasting or leptin
administration: cross-sectional and interventional studies in normal, insulin-resistant, and diabetic
subjects. J Clin Endocrinol Metab 2003; 88(10):4848–4856.
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 67
136. Silha JV, Krsek M, Hana V, Marek J, Jezkova J, Weiss V et al. Perturbations in adiponectin, leptin
and resistin levels in acromegaly: lack of correlation with insulin resistance. Clin Endocrinol (Oxf)
2003; 58(6):736–742.
137. Banerjee RR, Rangwala SM, Shapiro JS, Rich AS, Rhoades B, Qi Y et al. Regulation of fasted blood
glucose by resistin. Science 2004; 303(5661):1195–1198.
138. Lee JH, Bullen JW, Jr, Stoyneva VL, Mantzoros CS. Circulating resistin in lean, obese, and insulin-
resistant mouse models: lack of association with insulinemia and glycemia. Am J Physiol Endocrinol
Metab 2005; 288(3):E625–E632.
139. Barb D, Pazaitou-Panayiotou K, Mantzoros CS. Adiponectin: a link between obesity and cancer.
Expert Opin Invest Drugs 2006; 15(8):917–931.
140. Tovar S, Nogueiras R, Tung LY, Castaneda TR, Vazquez MJ, Morris A et al. Central administration
of resistin promotes short-term satiety in rats. Eur J Endocrinol 2005; 153(3):R1–R5.
141. O’Dowd BF, Heiber M, Chan A, Heng HH, Tsui LC, Kennedy JL et al. A human gene that shows
identity with the gene encoding the angiotensin receptor is located on chromosome 11. Gene 1993;
136(1–2):355–360.
142. Boucher J, Masri B, Daviaud D, Gesta S, Guigne C, Mazzucotelli A et al. Apelin, a newly identified
adipokine up-regulated by insulin and obesity. Endocrinology 2005; 146(4):1764–1771.
143. Beltowski J. Apelin and visfatin: unique “beneficial” adipokines upregulated in obesity? Med Sci
Monit 2006; 12(6):RA112–RA119.
144. Taheri S, Murphy K, Cohen M, Sujkovic E, Kennedy A, Dhillo W et al. The effects of centrally
administered apelin-13 on food intake, water intake and pituitary hormone release in rats. Biochem
Biophys Res Commun 2002; 291(5):1208–1212.
145. Sunter D, Hewson AK, Dickson SL. Intracerebroventricular injection of apelin-13 reduces food intake
in the rat. Neurosci Lett 2003; 353(1):1–4.
146. O’Shea M, Hansen MJ, Tatemoto K, Morris MJ. Inhibitory effect of apelin-12 on nocturnal food intake
in the rat. Nutr Neurosci 2003; 6(3):163–167.
147. Fukuhara A, Matsuda M, Nishizawa M, Segawa K, Tanaka M, Kishimoto K et al. Visfatin: a protein
secreted by visceral fat that mimics the effects of insulin. Science 2005; 307(5708):426–430.
148. Berndt J, Kloting N, Kralisch S, Kovacs P, Fasshauer M, Schon MR et al. Plasma visfatin concentra-
tions and fat depot-specific mRNA expression in humans. Diabetes 2005; 54(10):2911–2916.
149. Chen MP, Chung FM, Chang DM, Tsai JC, Huang HF, Shin SJ et al. Elevated plasma level of visfatin/
pre-B cell colony-enhancing factor in patients with type 2 diabetes mellitus. J Clin Endocrinol Metab
2006; 91(1):295–299.
150. Hammarstedt A, Pihlajamaki J, Rotter SV, Gogg S, Jansson PA, Laakso M et al. Visfatin is an
adipokine, but it is not regulated by thiazolidinediones. J Clin Endocrinol Metab 2006; 91(3):1181–
1184.
151. Pagano C, Pilon C, Olivieri M, Mason P, Fabris R, Serra R et al. Reduced plasma visfatin/pre-B cell
colony-enhancing factor in obesity is not related to insulin resistance in humans. J Clin Endocrinol
Metab 2006; 91(8):3165–3170.
152. Warne JP. Tumour necrosis factor alpha: a key regulator of adipose tissue mass. J Endocrinol 2003;
177(3):351–355.
153. Niswender KD, Schwartz MW. Insulin and leptin revisited: adiposity signals with overlapping physi-
ological and intracellular signaling capabilities. Front Neuroendocrinol 2003; 24(1):1–10.
154. Marks JL, Porte D, Jr, Stahl WL, Baskin DG. Localization of insulin receptor mRNA in rat brain by
in situ hybridization. Endocrinology 1990; 127(6):3234–3236.
155. Woods SC, Lotter EC, McKay LD, Porte D, Jr. Chronic intracerebroventricular infusion of insulin
reduces food intake and body weight of baboons. Nature 1979; 282(5738):503–505.
156. Bruning JC, Gautam D, Burks DJ, Gillette J, Schubert M, Orban PC et al. Role of brain insulin recep-
tor in control of body weight and reproduction. Science 2000; 289(5487):2122–2125.
157. Cohen P, Zhao C, Cai X, Montez JM, Rohani SC, Feinstein P et al. Selective deletion of leptin receptor
in neurons leads to obesity. J Clin Invest 2001; 108(8):1113–1121.
158. Kaiyala KJ, Prigeon RL, Kahn SE, Woods SC, Schwartz MW. Obesity induced by a high-fat diet is
associated with reduced brain insulin transport in dogs. Diabetes 2000; 49(9):1525–1533.
159. Benoit SC, Air EL, Coolen LM, Strauss R, Jackman A, Clegg DJ et al. The catabolic action of insulin
in the brain is mediated by melanocortins. J Neurosci 2002; 22(20):9048–9052.
68 Kelesidis, Kelesidis, and Mantzoros
160. Schwartz MW, Sipols AJ, Marks JL, Sanacora G, White JD, Scheurink A et al. Inhibition of hypotha-
lamic neuropeptide Y gene expression by insulin. Endocrinology 1992; 130(6):3608–3616.
161. White JD, Olchovsky D, Kershaw M, Berelowitz M. Increased hypothalamic content of preprone-
uropeptide-Y messenger ribonucleic acid in streptozotocin-diabetic rats. Endocrinology 1990;
126(2):765–772.
162. Bagdade JD, Bierman EL, Porte D, Jr. The significance of basal insulin levels in the evaluation of the insu-
lin response to glucose in diabetic and nondiabetic subjects. J Clin Invest 1967; 46(10):1549–1557.
163. Larsson LI, Sundler F, Hakanson R. Immunohistochemical localization of human pancreatic polypep-
tide (HPP) to a population of islet cells. Cell Tissue Res 1975; 156(2):167–171.
164. Asakawa A, Inui A, Yuzuriha H, Ueno N, Katsuura G, Fujimiya M et al. Characterization of the effects of
pancreatic polypeptide in the regulation of energy balance. Gastroenterology 2003; 124(5):1325–1336.
165. Whitcomb DC, Taylor IL, Vigna SR. Characterization of saturable binding sites for circulating pan-
creatic polypeptide in rat brain. Am J Physiol 1990; 259(4 Pt 1):G687–G691.
166. Hwang JJ, Chan JL, Ntali G, Malkova D, Mantzoros CS. Leptin does not directly regulate the pancreatic
hormones, amylin and pancreatic polypeptide: interventional studies in humans. Diabetes Care 2008;
31:945–951.
167. Ueno N, Inui A, Iwamoto M, Kaga T, Asakawa A, Okita M et al. Decreased food intake and body
weight in pancreatic polypeptide-overexpressing mice. Gastroenterology 1999; 117(6):1427–1432.
168. Malaisse-Lagae F, Carpentier JL, Patel YC, Malaisse WJ, Orci L. Pancreatic polypeptide: a possible
role in the regulation of food intake in the mouse. Hypothesis. Experientia 1977; 33(7):915–917.
169. McLaughlin CL, Baile CA. Obese mice and the satiety effects of cholecystokinin, bombesin and
pancreatic polypeptide. Physiol Behav 1981; 26(3):433–437.
170. Batterham RL, Le Roux CW, Cohen MA, Park AJ, Ellis SM, Patterson M et al. Pancreatic polypeptide
reduces appetite and food intake in humans. J Clin Endocrinol Metab 2003; 88(8):3989–3992.
171. Berntson GG, Zipf WB, O’Dorisio TM, Hoffman JA, Chance RE. Pancreatic polypeptide infusions
reduce food intake in Prader–Willi syndrome. Peptides 1993; 14(3):497–503.
172. Clark JT, Kalra PS, Crowley WR, Kalra SP. Neuropeptide Y and human pancreatic polypeptide
stimulate feeding behavior in rats. Endocrinology 1984; 115(1):427–429.
173. Fujimoto S, Inui A, Kiyota N, Seki W, Koide K, Takamiya S et al. Increased cholecystokinin and
pancreatic polypeptide responses to a fat-rich meal in patients with restrictive but not bulimic anorexia
nervosa. Biol Psychiatry 1997; 41(10):1068–1070.
174. Uhe AM, Szmukler GI, Collier GR, Hansky J, O’Dea K, Young GP. Potential regulators of feeding
behavior in anorexia nervosa. Am J Clin Nutr 1992; 55(1):28–32.
175. Glaser B, Zoghlin G, Pienta K, Vinik AI. Pancreatic polypeptide response to secretin in obesity: effects
of glucose intolerance. Horm Metab Res 1988; 20(5):288–292.
176. Lassmann V, Vague P, Vialettes B, Simon MC. Low plasma levels of pancreatic polypeptide in obesity.
Diabetes 1980; 29(6):428–430.
177. Zipf WB, O’Dorisio TM, Cataland S, Dixon K. Pancreatic polypeptide responses to protein meal
challenges in obese but otherwise normal children and obese children with Prader–Willi syndrome.
J Clin Endocrinol Metab 1983; 57(5):1074–1080.
178. Zipf WB, O’Dorisio TM, Cataland S, Sotos J. Blunted pancreatic polypeptide responses in children
with obesity of Prader–Willi syndrome. J Clin Endocrinol Metab 1981; 52(6):1264–1266.
179. Meryn S, Stein D, Straus EW. Fasting- and meal-stimulated peptide hormone concentrations before
and after gastric surgery for morbid obesity. Metabolism 1986; 35(9):798–802.
180. Wisen O, Bjorvell H, Cantor P, Johansson C, Theodorsson E. Plasma concentrations of regulatory
peptides in obesity following modified sham feeding (MSF) and a liquid test meal. Regul Pept 1992;
39(1):43–54.
181. Marco J, Zulueta MA, Correas I, Villanueva ML. Reduced pancreatic polypeptide secretion in obese
subjects. J Clin Endocrinol Metab 1980; 50(4):744–747.
182. Koska J, DelParigi A, de Court, Weyer C, Tataranni PA. Pancreatic polypeptide is involved in the
regulation of body weight in Pima Indian male subjects. Diabetes 2004; 53(12):3091–3096.
183. Lutz TA. Amylinergic control of food intake. Physiol Behav 2006.
184. Lutz TA, Mollet A, Rushing PA, Riediger T, Scharrer E. The anorectic effect of a chronic peripheral
infusion of amylin is abolished in area postrema/nucleus of the solitary tract (AP/NTS) lesioned rats.
Int J Obes Relat Metab Disord 2001; 25(7):1005–1011.
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 69
185. Rushing PA, Hagan MM, Seeley RJ, Lutz TA, D’Alessio DA, Air EL et al. Inhibition of central amylin
signaling increases food intake and body adiposity in rats. Endocrinology 2001; 142(11):5035.
186. Woods SC, Lutz TA, Geary N, Langhans W. Pancreatic signals controlling food intake; insulin, glu-
cagon and amylin. Philos Trans R Soc Lond B Biol Sci 2006; 361(1471):1219–1235.
187. Rushing PA. Central amylin signaling and the regulation of energy homeostasis. Curr Pharm Des
2003; 9(10):819–825.
188. Reidelberger RD, Kelsey L, Heimann D. Effects of amylin-related peptides on food intake,
meal patterns, and gastric emptying in rats. Am J Physiol Regul Integr Comp Physiol 2002;
282(5):R1395–R1404.
189. Osto M, Wielinga PY, Alder B, Walser N, Lutz TA. Modulation of the satiating effect of amylin by
central ghrelin, leptin and insulin. Physiol Behav 2007; 91(5):566–572.
190. Roth JD, Hughes H, Kendall E, Baron AD, Anderson CM. Antiobesity effects of the beta-cell hor-
mone amylin in diet-induced obese rats: effects on food intake, body weight, composition, energy
expenditure, and gene expression. Endocrinology 2006; 147(12):5855–5864.
191. Schmitz O, Brock B, Rungby J. Amylin agonists: a novel approach in the treatment of diabetes. Dia-
betes 2004; 53(Suppl 3):S233–S238.
192. Hollander P, Maggs DG, Ruggles JA, Fineman M, Shen L, Kolterman OG et al. Effect of pram-
lintide on weight in overweight and obese insulin-treated type 2 diabetes patients. Obes Res 2004;
12(4):661–668.
193. Hollander P, Maggs DG, Ruggles JA, Fineman M, Shen L, Kolterman OG et al. Effect of pramlintide on
weight in overweight and obese insulin-treated type 2 diabetes patients. Obes Res 2004; 12(4):661–668.
194. Aronne L, Fujioka K, Aroda V, Chen K, Halseth A, Kesty NC et al. Progressive reduction in body
weight after treatment with the amylin analog pramlintide in obese subjects: a phase 2, randomized,
placebo-controlled, dose-escalation study. J Clin Endocrinol Metab 2007; 92(8):2977–2983.
195. Kojima M, Hosoda H, Date Y, Nakazato M, Matsuo H, Kangawa K. Ghrelin is a growth-hormone-
releasing acylated peptide from stomach. Nature 1999; 402(6762):656–660.
196. Toshinai K, Date Y, Murakami N, Shimada M, Mondal MS, Shimbara T et al. Ghrelin-induced food
intake is mediated via the orexin pathway. Endocrinology 2003; 144(4):1506–1512.
197. Cummings DE, Purnell JQ, Frayo RS, Schmidova K, Wisse BE, Weigle DS. A preprandial rise in plasma
ghrelin levels suggests a role in meal initiation in humans. Diabetes 2001; 50(8):1714–1719.
198. Cummings DE, Weigle DS, Frayo RS, Breen PA, Ma MK, Dellinger EP et al. Plasma ghrelin levels
after diet-induced weight loss or gastric bypass surgery. N Engl J Med 2002; 346(21):1623–1630.
199. Cummings DE, Frayo RS, Marmonier C, Aubert R, Chapelot D. Plasma ghrelin levels and hunger scores
in humans initiating meals voluntarily without time- and food-related cues. Am J Physiol Endocrinol
Metab 2004; 287(2):E297–E304.
200. Tschop M, Weyer C, Tataranni PA, Devanarayan V, Ravussin E, Heiman ML. Circulating ghrelin
levels are decreased in human obesity. Diabetes 2001; 50(4):707–709.
201. English PJ, Ghatei MA, Malik IA, Bloom SR, Wilding JP. Food fails to suppress ghrelin levels in
obese humans. J Clin Endocrinol Metab 2002; 87(6):2984.
202. Chan JL, Bullen J, Lee JH, Yiannakouris N, Mantzoros CS. Ghrelin levels are not regulated by recom-
binant leptin administration and/or three days of fasting in healthy subjects. J Clin Endocrinol Metab
2004; 89(1):335–343.
203. Nakazato M, Murakami N, Date Y, Kojima M, Matsuo H, Kangawa K et al. A role for ghrelin in the
central regulation of feeding. Nature 2001; 409(6817):194–198.
204. Wren AM, Small CJ, Abbott CR, Dhillo WS, Seal LJ, Cohen MA et al. Ghrelin causes hyperphagia
and obesity in rats. Diabetes 2001; 50(11):2540–2547.
205. Wren AM, Seal LJ, Cohen MA, Brynes AE, Frost GS, Murphy KG et al. Ghrelin enhances appetite
and increases food intake in humans. J Clin Endocrinol Metab 2001; 86(12):5992.
206. Zigman JM, Nakano Y, Coppari R, Balthasar N, Marcus JN, Lee CE et al. Mice lacking ghrelin recep-
tors resist the development of diet-induced obesity. J Clin Invest 2005; 115(12):3564–3572.
207. Wortley KE, del Rincon JP, Murray JD, Garcia K, Iida K, Thorner MO et al. Absence of ghrelin
protects against early-onset obesity. J Clin Invest 2005; 115(12):3573–3578.
208. Wortley KE, Anderson KD, Garcia K, Murray JD, Malinova L, Liu R et al. Genetic deletion of ghrelin
does not decrease food intake but influences metabolic fuel preference. Proc Natl Acad Sci USA 2004;
101(21):8227–8232.
70 Kelesidis, Kelesidis, and Mantzoros
209. Sun Y, Ahmed S, Smith RG. Deletion of ghrelin impairs neither growth nor appetite. Mol Cell Biol
2003; 23(22):7973–7981.
210. Sun Y, Wang P, Zheng H, Smith RG. Ghrelin stimulation of growth hormone release and appetite
is mediated through the growth hormone secretagogue receptor. Proc Natl Acad Sci USA 2004;
101(13):4679–4684.
211. Dong J, Peeters TL, De Smet B, Moechars D, Delporte C, Vanden Berghe P et al. Role of endog-
enous ghrelin in the hyperphagia of mice with streptozotocin-induced diabetes. Endocrinology 2006;
147(6):2634–2642.
212. Sun Y, Asnicar M, Saha PK, Chan L, Smith RG. Ablation of ghrelin improves the diabetic but not
obese phenotype of ob/ob mice. Cell Metab 2006; 3(5):379–386.
213. Neary NM, Small CJ, Wren AM, Lee JL, Druce MR, Palmieri C et al. Ghrelin increases energy intake
in cancer patients with impaired appetite: acute, randomized, placebo-controlled trial. J Clin Endocrinol
Metab 2004; 89(6):2832–2836.
214. Wynne K, Giannitsopoulou K, Small CJ, Patterson M, Frost G, Ghatei MA et al. Subcutaneous ghrelin
enhances acute food intake in malnourished patients who receive maintenance peritoneal dialysis: a
randomized, placebo-controlled trial. J Am Soc Nephrol 2005; 16(7):2111–2118.
215. Tatemoto K, Mutt V. Isolation of two novel candidate hormones using a chemical method for finding
naturally occurring polypeptides. Nature 1980; 285(5764):417–418.
216. Adrian TE, Ferri GL, Bacarese-Hamilton AJ, Fuessl HS, Polak JM, Bloom SR. Human distribution
and release of a putative new gut hormone, peptide YY. Gastroenterology 1985; 89(5):1070–1077.
217. Tatemoto K, Carlquist M, Mutt V. Neuropeptide Y – a novel brain peptide with structural similarities
to peptide YY and pancreatic polypeptide. Nature 1982; 296(5858):659–660.
218. Anini Y, Fu-Cheng X, Cuber JC, Kervran A, Chariot J, Roz C. Comparison of the postprandial release
of peptide YY and proglucagon-derived peptides in the rat. Pflugers Arch 1999; 438(3):299–306.
219. Korner J, Leibel RL. To eat or not to eat – how the gut talks to the brain. N Engl J Med 2003;
349(10):926–928.
220. Challis BG, Coll AP, Yeo GS, Pinnock SB, Dickson SL, Thresher RR et al. Mice lacking pro-opi-
omelanocortin are sensitive to high-fat feeding but respond normally to the acute anorectic effects of
peptide-YY(3-36). Proc Natl Acad Sci USA 2004; 101(13):4695–4700.
221. Pittner RA, Moore CX, Bhavsar SP, Gedulin BR, Smith PA, Jodka CM et al. Effects of PYY[3–36]
in rodent models of diabetes and obesity. Int J Obes Relat Metab Disord 2004; 28(8):963–971.
222. Degen L, Oesch S, Casanova M, Graf S, Ketterer S, Drewe J et al. Effect of peptide YY3-36 on food
intake in humans. Gastroenterology 2005; 129(5):1430–1436.
223. Chelikani PK, Haver AC, Reidelberger RD. Intravenous infusion of peptide YY (3–36) potently inhibits
food intake in rats. Endocrinology 2005; 146(2):879–888.
224. Batterham RL, Cowley MA, Small CJ, Herzog H, Cohen MA, Dakin CL et al. Gut hormone PYY(3–36)
physiologically inhibits food intake. Nature 2002; 418(6898):650–654.
225. Sileno AP, Brandt GC, Spann BM, Quay SC. Lower mean weight after 14 days intravenous adminis-
tration peptide YY3–36 (PYY3–36) in rabbits. Int J Obes (Lond) 2006; 30(1):68–72.
226. Corp ES, McQuade J, Krasnicki S, Conze DB. Feeding after fourth ventricular administration of
neuropeptide Y receptor agonists in rats. Peptides 2001; 22(3):493–499.
227. Hagan MM, Castaneda E, Sumaya IC, Fleming SM, Galloway J, Moss DE. The effect of hypothalamic
peptide YY on hippocampal acetylcholine release in vivo: implications for limbic function in binge-
eating behavior. Brain Res 1998; 805(1/2):20–28.
228. Batterham RL, Cohen MA, Ellis SM, Le Roux CW, Withers DJ, Frost GS et al. Inhibition of food
intake in obese subjects by peptide YY3-36. N Engl J Med 2003; 349(10):941–948.
229. Chan JL, Stoyneva V, Kelesidis T, Raciti P, Mantzoros CS. Peptide YY levels are decreased by
fasting and elevated following caloric intake but are not regulated by leptin. Diabetologia 2006;
49(1):169–173.
230. Chan JL, Mun EC, Stoyneva V, Mantzoros CS, Goldfine AB. Peptide YY levels are elevated after
gastric bypass surgery. Obesity (Silver Spring) 2006; 14(2):194–198.
231. Halford JC. Obesity drugs in clinical development. Curr Opin Invest Drugs 2006; 7(4):312–318.
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 71
232. Drucker DJ, Philippe J, Mojsov S, Chick WL, Habener JF. Glucagon-like peptide I stimulates insulin
gene expression and increases cyclic AMP levels in a rat islet cell line. Proc Natl Acad Sci USA 1987;
84(10):3434–3438.
233. Tang-Christensen M, Vrang N, Larsen PJ. Glucagon-like peptide containing pathways in the regulation
of feeding behaviour. Int J Obes Relat Metab Disord 2001; 25(Suppl 5):S42–S47.
234. Turton MD, O’Shea D, Gunn I, Beak SA, Edwards CM, Meeran K et al. A role for glucagon-like
peptide-1 in the central regulation of feeding. Nature 1996; 379(6560):69–72.
235. Meeran K, O’Shea D, Edwards CM, Turton MD, Heath MM, Gunn I et al. Repeated intracerebroven-
tricular administration of glucagon-like peptide-1-(7-36) amide or exendin-(9-39) alters body weight
in the rat. Endocrinology 1999; 140(1):244–250.
236. Greig NH, Holloway HW, De Ore KA, Jani D, Wang Y, Zhou J et al. Once daily injection of exendin-4
to diabetic mice achieves long-term beneficial effects on blood glucose concentrations. Diabetologia
1999; 42(1):45–50.
237. Szayna M , Doyle ME , Betkey JA , Holloway HW, Spencer RG , Greig NH et al . Exendin-4
decelerates food intake, weight gain, and fat deposition in Zucker rats. Endocrinology 2000;
141(6):1936–1941.
238. Scrocchi LA, Hill ME, Saleh J, Perkins B, Drucker DJ. Elimination of glucagon-like peptide 1R sig-
naling does not modify weight gain and islet adaptation in mice with combined disruption of leptin
and GLP-1 action. Diabetes 2000; 49(9):1552–1560.
239. Scrocchi LA, Brown TJ, MaClusky N, Brubaker PL, Auerbach AB, Joyner AL et al. Glucose intoler-
ance but normal satiety in mice with a null mutation in the glucagon-like peptide 1 receptor gene. Nat
Med 1996; 2(11):1254–1258.
240. Meier JJ, Gallwitz B, Schmidt WE, Nauck MA. Glucagon-like peptide 1 as a regulator of food intake
and body weight: therapeutic perspectives. Eur J Pharmacol 2002; 440(2/3):269–279.
241. Verdich C, Flint A, Gutzwiller JP, Naslund E, Beglinger C, Hellstrom PM et al. A meta-analysis of
the effect of glucagon-like peptide-1 (7–36) amide on ad libitum energy intake in humans. J Clin
Endocrinol Metab 2001; 86(9):4382–4389.
242. Naslund E, King N, Mansten S, Adner N, Holst JJ, Gutniak M et al. Prandial subcutaneous injections of
glucagon-like peptide-1 cause weight loss in obese human subjects. Br J Nutr 2004; 91(3):439–446.
243. Bullock BP, Heller RS, Habener JF. Tissue distribution of messenger ribonucleic acid encoding the
rat glucagon-like peptide-1 receptor. Endocrinology 1996; 137(7):2968–2978.
244. Badman MK, Flier JS. The gut and energy balance: visceral allies in the obesity wars. Science 2005;
307(5717):1909–1914.
245. Schmidt PT, Naslund E, Gryback P, Jacobsson H, Hartmann B, Holst JJ et al. Peripheral administration
of GLP-2 to humans has no effect on gastric emptying or satiety. Regul Pept 2003; 116(1–3):21–25.
246. Miyawaki K, Yamada Y, Ban N, Ihara Y, Tsukiyama K, Zhou H et al. Inhibition of gastric inhibitory
polypeptide signaling prevents obesity. Nat Med 2002; 8(7):738–742.
247. Buse JB, Henry RR, Han J, Kim DD, Fineman MS, Baron AD. Effects of exenatide (exendin-4) on
glycemic control over 30 weeks in sulfonylurea-treated patients with type 2 diabetes. Diabetes Care
2004; 27(11):2628–2635.
248. DeFronzo RA, Ratner RE, Han J, Kim DD, Fineman MS, Baron AD. Effects of exenatide (exendin-4) on
glycemic control and weight over 30 weeks in metformin-treated patients with type 2 diabetes. Diabetes
Care 2005; 28(5):1092–1100.
249. Kendall DM, Riddle MC, Rosenstock J, Zhuang D, Kim DD, Fineman MS et al. Effects of exenatide
(exendin-4) on glycemic control over 30 weeks in patients with type 2 diabetes treated with metformin
and a sulfonylurea. Diabetes Care 2005; 28(5):1083–1091.
250. Kuehn BM. New diabetes drugs target gut hormones. JAMA 2006; 296(4):380–381.
251. Drucker DJ, Nauck MA. The incretin system: glucagon-like peptide-1 receptor agonists and dipeptidyl
peptidase-4 inhibitors in type 2 diabetes. Lancet 2006; 368(9548):1696–1705.
252. Ristic S, Byiers S, Foley J, Holmes D. Improved glycaemic control with dipeptidyl peptidase-4 inhi-
bition in patients with type 2 diabetes: vildagliptin (LAF237) dose response. Diabetes Obes Metab
2005; 7(6):692–698.
72 Kelesidis, Kelesidis, and Mantzoros
253. Charbonnel B, Karasik A, Liu J, Wu M, Meininger G. Efficacy and safety of the dipeptidyl peptidase-4
inhibitor sitagliptin added to ongoing metformin therapy in patients with type 2 diabetes inadequately
controlled with metformin alone. Diabetes Care 2006; 29(12):2638–2643.
254. Aschner P, Kipnes MS, Lunceford JK, Sanchez M, Mickel C, Williams-Herman DE. Effect of the
dipeptidyl peptidase-4 inhibitor sitagliptin as monotherapy on glycemic control in patients with type
2 diabetes. Diabetes Care 2006; 29(12):2632–2637.
255. Raz I, Hanefeld M, Xu L, Caria C, Williams-Herman D, Khatami H. Efficacy and safety of the
dipeptidyl peptidase-4 inhibitor sitagliptin as monotherapy in patients with type 2 diabetes mellitus.
Diabetologia 2006; 49(11):2564–2571.
256. Rosenstock J, Brazg R, Andryuk PJ, Lu K, Stein P. Efficacy and safety of the dipeptidyl peptidase-4
inhibitor sitagliptin added to ongoing pioglitazone therapy in patients with type 2 diabetes: a 24-week,
multicenter, randomized, double-blind, placebo-controlled, parallel-group study. Clin Ther 2006;
28(10):1556–1568.
257. Balas B, Baig MR, Watson C, Dunning BE, Ligueros-Saylan M, Wang Y et al. The dipeptidyl
peptidase IV inhibitor vildagliptin suppresses endogenous glucose production and enhances islet
function after single dose administration in type 2 diabetic patients. J Clin Endocrinol Metab 2007;
92(4):1249–1255.
258. Pi-Sunyer FX, Schweizer A, Mills D, Dejager S. Efficacy and tolerability of vildagliptin monotherapy
in drug-naive patients with type 2 diabetes. Diabetes Res Clin Pract 2007; 76(1):132–138.
259. Pratley RE, Jauffret-Kamel S, Galbreath E, Holmes D. Twelve-week monotherapy with the DPP-4
inhibitor vildagliptin improves glycemic control in subjects with type 2 diabetes. Horm Metab Res
2006; 38(6):423–428.
260. Le Quellec A, Kervran A, Blache P, Ciurana AJ, Bataille D. Oxyntomodulin-like immunoreactivity:
diurnal profile of a new potential enterogastrone. J Clin Endocrinol Metab 1992; 74(6):1405–1409.
261. Dakin CL, Gunn I, Small CJ, Edwards CM, Hay DL, Smith DM et al. Oxyntomodulin inhibits food
intake in the rat. Endocrinology 2001; 142(10):4244–4250.
262. Dakin CL, Small CJ, Batterham RL, Neary NM, Cohen MA, Patterson M et al. Peripheral oxyntomod-
ulin reduces food intake and body weight gain in rats. Endocrinology 2004; 145(6):2687–2695.
263. Cohen MA, Ellis SM, Le Roux CW, Batterham RL, Park A, Patterson M et al. Oxyntomodulin suppresses
appetite and reduces food intake in humans. J Clin Endocrinol Metab 2003; 88(10):4696–4701.
264. Wynne K, Park AJ, Small CJ, Patterson M, Ellis SM, Murphy KG et al. Subcutaneous oxyntomodulin
reduces body weight in overweight and obese subjects: a double-blind, randomized, controlled trial.
Diabetes 2005; 54(8):2390–2395.
265. Wynne K, Park AJ, Small CJ, Meeran K, Ghatei MA, Frost GS et al. Oxyntomodulin increases energy
expenditure in addition to decreasing energy intake in overweight and obese humans: a randomised
controlled trial. Int J Obes (Lond) 2006; 30(12):1729–1736.
266. Go VLW. The physiology of cholecystokinin. Gut hormones. Edinburgh: Chruchill Livingstone, 1978: 203.
267. Kissileff HR, Carretta JC, Geliebter A, Pi-Sunyer FX. Cholecystokinin and stomach distension com-
bine to reduce food intake in humans. Am J Physiol Regul Integr Comp Physiol 2003; 285(5):R992–
R998.
268. Moran TH, McHugh PR. Cholecystokinin suppresses food intake by inhibiting gastric emptying. Am
J Physiol 1982; 242(5):R491–R497.
269. Corp ES, Curcio M, Gibbs J, Smith GP. The effect of centrally administered CCK-receptor antagonists
on food intake in rats. Physiol Behav 1997; 61(6):823–827.
270. Beglinger C, Degen L, Matzinger D, D’Amato M, Drewe J. Loxiglumide, a CCK-A receptor antagonist,
stimulates calorie intake and hunger feelings in humans. Am J Physiol Regul Integr Comp Physiol
2001; 280(4):R1149–R1154.
271. West DB, Fey D, Woods SC. Cholecystokinin persistently suppresses meal size but not food intake
in free-feeding rats. Am J Physiol 1984; 246(5 Pt 2):R776–R787.
272. McLaughlin CL, Baile CA, Buonomo FC. Effect of CCK antibodies on food intake and weight gain
in Zucker rats. Physiol Behav 1985; 34(2):277–282.
273. Meereis-Schwanke K, Klonowski-Stumpe H, Herberg L, Niederau C. Long-term effects of CCK-
agonist and -antagonist on food intake and body weight in Zucker lean and obese rats. Peptides 1998;
19(2):291–299.
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 73
274. Matson CA, Reid DF, Cannon TA, Ritter RC. Cholecystokinin and leptin act synergistically to reduce
body weight. Am J Physiol Regul Integr Comp Physiol 2000; 278(4):R882–R890.
275. Merali Z, McIntosh J, Anisman H. Role of bombesin-related peptides in the control of food intake.
Neuropeptides 1999; 33(5):376–386.
276. Flynn FW. Fourth ventricular injection of selective bombesin receptor antagonists facilitates feeding
in rats. Am J Physiol 1993; 264(1 Pt 2):R218–R221.
277. Gutzwiller JP, Drewe J, Hildebrand P, Rossi L, Lauper JZ, Beglinger C. Effect of intravenous human
gastrin-releasing peptide on food intake in humans. Gastroenterology 1994; 106(5):1168–1173.
278. Battey JF, Way JM, Corjay MH, Shapira H, Kusano K, Harkins R et al. Molecular cloning of the
bombesin/gastrin-releasing peptide receptor from Swiss 3T3 cells. Proc Natl Acad Sci USA 1991;
88(2):395–399.
279. Gibbs J, Kulkosky PJ, Smith GP. Effects of peripheral and central bombesin on feeding behavior of
rats. Peptides 1981; 2(Suppl 2):179–183.
280. Gibbs J, Fauser DJ, Rowe EA, Rolls BJ, Rolls ET, Maddison SP. Bombesin suppresses feeding in rats.
Nature 1979; 282(5735):208–210.
281. Smith GP, Jerome C, Gibbs J. Abdominal vagotomy does not block the satiety effect of bombesin in
the rat. Peptides 1981; 2(4):409–411.
282. Lieverse RJ, Jansen JB, van de ZA, Samson L, Masclee AA, Rovati LC et al. Bombesin reduces food
intake in lean man by a cholecystokinin-independent mechanism. J Clin Endocrinol Metab 1993;
76(6):1495–1498.
283. Ohki-Hamazaki H, Watase K, Yamamoto K, Ogura H, Yamano M, Yamada K et al. Mice lacking bombe-
sin receptor subtype-3 develop metabolic defects and obesity. Nature 1997; 390(6656):165–169.
284. Green PH, Glickman RM, Riley JW, Quinet E. Human apolipoprotein A-IV. Intestinal origin and
distribution in plasma. J Clin Invest 1980; 65(4):911–919.
285. Liu M, Doi T, Shen L, Woods SC, Seeley RJ, Zheng S et al. Intestinal satiety protein apolipoprotein
AIV is synthesized and regulated in rat hypothalamus. Am J Physiol Regul Integr Comp Physiol 2001;
280(5):R1382–R1387.
286. Tso P, Liu M, Kalogeris TJ, Thomson AB. The role of apolipoprotein A-IV in the regulation of food
intake. Annu Rev Nutr 2001; 21:231–254.
287. Tso P, Liu M. Apolipoprotein A-IV, food intake, and obesity. Physiol Behav 2004; 83(4):631–643.
288. Tso P, Liu M. Ingested fat and satiety. Physiol Behav 2004; 81(2):275–287.
289. Fujimoto K, Machidori H, Iwakiri R, Yamamoto K, Fujisaki J, Sakata T et al. Effect of intravenous
administration of apolipoprotein A-IV on patterns of feeding, drinking and ambulatory activity of rats.
Brain Res 1993; 608(2):233–237.
290. Fujimoto K, Fukagawa K, Sakata T, Tso P. Suppression of food intake by apolipoprotein A-IV is
mediated through the central nervous system in rats. J Clin Invest 1993; 91(4):1830–1833.
291. Erlanson-Albertsson C, York D. Enterostatin – a peptide regulating fat intake. Obes Res 1997;
5(4):360–372.
292. York DA, Lin L, Thomas SR, Braymer HD, Park M. Procolipase gene expression in the rat brain:
source of endogenous enterostatin production in the brain. Brain Res 2006; 1087(1):52–59.
293. Okada S, York DA, Bray GA, Erlanson-Albertsson C. Enterostatin (Val-Pro-Asp-Pro-Arg), the activation
peptide of procolipase, selectively reduces fat intake. Physiol Behav 1991; 49(6):1185–1189.
294. Ookuma K, Barton C, York DA, Bray GA. Effect of enterostatin and kappa-opioids on macronutrient
selection and consumption. Peptides 1997; 18(6):785–791.
295. Lin L, Umahara M, York DA, Bray GA. Beta-casomorphins stimulate and enterostatin inhibits the
intake of dietary fat in rats. Peptides 1998; 19(2):325–331.
296. Nogueiras R, Tschop M. Biomedicine. Separation of conjoined hormones yields appetite rivals.
Science 2005; 310(5750):985–986.
297. Zhang JV, Ren PG, Avsian-Kretchmer O, Luo CW, Rauch R, Klein C et al. Obestatin, a peptide encoded
by the ghrelin gene, opposes ghrelin’s effects on food intake. Science 2005; 310(5750):996–999.
298. Nogueiras R, Pfluger P, Tovar S, Arnold M, Mitchell S, Morris A et al. Effects of obestatin on energy
balance and growth hormone secretion in rodents. Endocrinology 2007; 148(1):21–26.
299. Holst B, Egerod KL, Schild E, Vickers SP, Cheetham S, Gerlach LO et al. GPR39 signaling is stimu-
lated by zinc ions but not by obestatin. Endocrinology 2007; 148(1):13–20.
74 Kelesidis, Kelesidis, and Mantzoros
300. Gale SM, Castracane VD, Mantzoros CS. Energy homeostasis, obesity and eating disorders: recent
advances in endocrinology. J Nutr 2004; 134(2):295–298.
301. Collins S, Kuhn CM, Petro AE, Swick AG, Chrunyk BA, Surwit RS. Role of leptin in fat regulation.
Nature 1996; 380(6576):677.
302. Haynes WG, Morgan DA, Walsh SA, Mark AL, Sivitz WI. Receptor-mediated regional sympathetic
nerve activation by leptin. J Clin Invest 1997; 100(2):270–278.
303. Hucking K, Hamilton-Wessler M, Ellmerer M, Bergman RN. Burst-like control of lipolysis by the
sympathetic nervous system in vivo. J Clin Invest 2003; 111(2):257–264.
304. Halaas JL, Boozer C, Blair-West J, Fidahusein N, Denton DA, Friedman JM. Physiological response
to long-term peripheral and central leptin infusion in lean and obese mice. Proc Natl Acad Sci USA
1997; 94(16):8878–8883.
305. Chan JL, Mietus JE, Raciti PM, Goldberger AL, Mantzoros CS. Short-term fasting-induced autonomic
activation and changes in catecholamine levels are not mediated by changes in leptin levels in healthy
humans. Clin Endocrinol (Oxf) 2007; 66(1):49–57.
306. Kamohara S, Burcelin R, Halaas JL, Friedman JM, Charron MJ. Acute stimulation of glucose me-
tabolism in mice by leptin treatment. Nature 1997; 389(6649):374–377.
307. Haque MS, Minokoshi Y, Hamai M, Iwai M, Horiuchi M, Shimazu T. Role of the sympathetic nervous
system and insulin in enhancing glucose uptake in peripheral tissues after intrahypothalamic injection
of leptin in rats. Diabetes 1999; 48(9):1706–1712.
308. Minokoshi Y, Haque MS, Shimazu T. Microinjection of leptin into the ventromedial hypothalamus
increases glucose uptake in peripheral tissues in rats. Diabetes 1999; 48(2):287–291.
309. Bates SH, Dundon TA, Seifert M, Carlson M, Maratos-Flier E, Myers MG, Jr. LRb-STAT3 signal-
ing is required for the neuroendocrine regulation of energy expenditure by leptin. Diabetes 2004;
53(12):3067–3073.
310. Lee JH, Chan JL, Sourlas E, Raptopoulos V, Mantzoros CS. r-metHuLeptin therapy in replacement
doses improves insulin resistance and metabolic profile in patients with lipoatrophy and metabolic
syndrome induced by the highly active antiretroviral therapy (HAART). J Clin Endocrinol Metab 2006;
91(7):2605–2611.
311. Oral EA, Simha V, Ruiz E, Andewelt A, Premkumar A, Snell P et al. Leptin-replacement therapy for
lipodystrophy. N Engl J Med 2002; 346(8):570–578.
312. Papathanassoglou E, El Haschimi K, Li XC, Matarese G, Strom T, Mantzoros C. Leptin receptor
expression and signaling in lymphocytes: kinetics during lymphocyte activation, role in lymphocyte
survival, and response to high fat diet in mice. J Immunol 2006; 176(12):7745–7752.
313. Chan JL, Moschos SJ, Bullen J, Heist K, Li X, Kim YB et al. Recombinant methionyl human leptin
administration activates signal transducer and activator of transcription 3 signaling in peripheral
blood mononuclear cells in vivo and regulates soluble tumor necrosis factor-{alpha} receptor levels
in humans with relative leptin deficiency. J Clin Endocrinol Metab 2005; 90(3):1625–1631.
314. Matarese G, Moschos S, Mantzoros CS. Leptin in immunology. J Immunol 2005; 174(6):3137–3142.
315. Strobel A, Issad T, Camoin L, Ozata M, Strosberg AD. A leptin missense mutation associated with
hypogonadism and morbid obesity. Nat Genet 1998; 18(3):213–215.
316. Farooqi IS, Jebb SA, Langmack G, Lawrence E, Cheetham CH, Prentice AM et al. Effects of recombinant
leptin therapy in a child with congenital leptin deficiency. N Engl J Med 1999; 341(12):879–884.
317. Ozata M, Ozdemir IC, Licinio J. Human leptin deficiency caused by a missense mutation: multiple
endocrine defects, decreased sympathetic tone, and immune system dysfunction indicate new targets
for leptin action, greater central than peripheral resistance to the effects of leptin, and spontaneous
correction of leptin-mediated defects. J Clin Endocrinol Metab 1999; 84(10):3686–3695.
318. Mantzoros CS. The role of leptin in human obesity and disease: a review of current evidence. Ann
Intern Med 1999; 130(8):671–680.
319. Munzberg H, Myers MG, Jr. Molecular and anatomical determinants of central leptin resistance. Nat
Neurosci 2005; 8(5):566–570.
320. Bjorbaek C, Elmquist JK, Frantz JD, Shoelson SE, Flier JS. Identification of SOCS-3 as a potential
mediator of central leptin resistance. Mol Cell 1998; 1(4):619–625.
321. El Haschimi K, Lehnert H. Leptin resistance – or why leptin fails to work in obesity. Exp Clin Endo-
crinol Diabetes 2003; 111(1):2–7.
Chapter 3 / Environmental Inputs, Intake of Nutrients, and Endogenous Molecules 75
322. Farooqi IS, Keogh JM, Kamath S, Jones S, Gibson WT, Trussell R et al. Partial leptin deficiency and
human adiposity. Nature 2001; 414(6859):34–35.
323. Chan JL, Bluher S, Yiannakouris N, Suchard MA, Kratzsch J, Mantzoros CS. Regulation of circu-
lating soluble leptin receptor levels by gender, adiposity, sex steroids, and leptin: observational and
interventional studies in humans. Diabetes 2002; 51(7):2105–2112.
324. Boden G, Chen X, Mozzoli M, Ryan I. Effect of fasting on serum leptin in normal human subjects.
J Clin Endocrinol Metab 1996; 81(9):3419–3423.
325. Jimerson DC, Mantzoros C, Wolfe BE, Metzger ED. Decreased serum leptin in bulimia nervosa.
J Clin Endocrinol Metab 2000; 85(12):4511–4514.
326. Audi L, Mantzoros CS, Vidal-Puig A, Vargas D, Gussinye M, Carrascosa A. Leptin in relation to
resumption of menses in women with anorexia nervosa. Mol Psychiatry 1998; 3(6):544–547.
4 Central Integration of Environmental
and Endogenous Signals Important
in the Regulation of Food Intake
and Energy Expenditure
Iosif Kelesidis, Theodore Kelesidis,
and Christos S. Mantzoros
KEY POINTS
• The worsening global epidemic of obesity has necessitated intensification of research into the
mechanisms of appetite regulation.
• Obesity can be viewed as the result of a classic gene–environment interaction where the
human genotype is susceptible to environmental influences that affect energy intake and
energy expenditure. The obesity epidemic can also be viewed as a problem of energy balance.
• Food intake and energy expenditure are processes dependent on information relayed to a
central network of sensing and processing neurons through hard-wired neural, metabolic, and
hormonal signals from the periphery.
• Complex pathways that modulate energy balance involve mainly hormonal signals released
by the gut and other organs in the periphery that convey information on energy status, as well
as appetite centers in the hypothalamus and brain stem.
• Our understanding of the neuronal pathways that initiate changes in ingestive behavior or
energy expenditure as well as our knowledge of the detailed signaling modalities underlying
central body weight regulation still remain largely unknown.
• Careful clarification of how behavioral and environmental factors interact to produce energy
balance (and in states of energy excess how the system fails to achieve energy balance, with
the end result being weight gain) is required in order to understand the etiology of obesity.
• Modification of a combination of these factors may be able to reverse the epidemic of obesity
and help the population achieve energy balance and a healthy body weight.
• The purpose of this chapter is to summarize our current understanding of the central pathways
regulating energy homeostasis. These neuronal pathways in the central nervous system
receive and integrate signals from the periphery that convey information about the status
of energy fluxes and stores. Understanding these mechanisms will provide insights for the
development of new treatment options for obesity.
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_4,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
77
78 Kelesidis, Kelesidis, Mantzoros
Key Words: Obesity, Energy homeostasis, Energy expenditure, Signals
1. CENTRAL REGULATION OF ENERGY HOMEOSTASIS
Discovery of the fat hormone leptin as part of an “adipostatic” endocrine system of
body weight regulation has elucidated our understanding of body weight homeostasis
(1) and has increased our knowledge of how peripheral endocrine organs and the central
nervous system (CNS) interact in the control of energy homeostasis. Peripherally
generated signals are integrated in the brain in a complex manner, resulting in
activation of both anorexigenic and orexigenic pathways to regulate energy balance.
The molecular elucidation of this complex system has improved our understanding of
energy homeostasis.
Peripheral signals such as nutrients (mainly lipids and carbohydrates) participate in
the regulation of energy homeostasis by activation of intracellular second messenger
pathways through surface enzymes (2) and ion channels (3,4) expressed in hypothalamic
neurons. In addition, the short-term regulation of feeding is accomplished by conduction
of information from chemoreceptors (mainly CCK) or stretch receptors to brainstem
through neural afferent signals from the periphery, conveyed mainly via the vagus nerve,
which innervates densely the gastrointestinal tract (Fig. 1). All these peripheral signals are
integrated in the CNS through complex neural structures, which are described below.
1.1. Structures in the CNS Mediating Energy Homeostasis
The hypothalamus plays a central role in the integration of peripheral signals in the
current energy homeostasis model (2). Within the hypothalamus, the arcuate nucleus
(ARC) is a major site of peripheral signal integration, as it is considered to be the key
sensor of peripheral energy input (reviewed in (3)).
Peripheral signals act mainly on two distinct neuronal populations. One population co-
expresses the orexigenic neuropeptides agouti-related peptide (AgRP) and neuropeptide
Y (NPY); the other population releases cocaine- and amphetamine-regulated transcript
and pro-opiomelanocortin, both of which inhibit feeding (Fig. 1). Both of these popula-
tions project to the paraventricular nucleus (PVN) and other nuclei involved in energy
regulation (4,5).
In states of positive energy balance, neurochemical signaling inhibits orexigenic cent-
ers and activates anorexigenic centers, while during negative energy states the opposite
occurs. Energy-modulating neuropeptides as well as receptors for peripheral hormones,
including leptin and insulin, as well as several sensors of nutrient intake and expenditure
have been identified in brain stem neurons (3). Therefore, the brain stem appears to also
play an important role in the integration of signals of energy availability (6). Obviously,
the energy homeostasis circuit is controlled at several levels and not only in the CNS.
1.2. Hypothalamic Structure and Neuronal Pathways Regulating Appetite
Most individuals maintain stable body weight over long periods of time despite wide
daily variations of food intake and energy expenditure (EE). For this to happen, food
intake and EE must be constantly adjusted and precisely balanced over time. Currently,
the emphasis in the regulation of body weight and endocrine function is placed on neuronal
circuits, composed of specific neuropeptides, rather than specific hypothalamic nuclei
that have been thought to play a major role in the past (see Fig. 1).
Chapter 4 / Central Integration of Environmental and Endogenous Signals 79
Fig. 1. Integration of peripheral signals in the hypothalamus and the central nervous system.
The interaction between the various components of this complex system is noted, as are the
neuropeptides that are expressed in each part of this complex circuit. ARC arcuate nucleus, AVP
vasopressin, AgRP agouti related protein, CART cocaine- and amphetamine-regulated transcript,
CCK cholecystokinin, CRH corticotropin releasing hormone, DMN dorsomedial nucleus, DRN
dorsal reticular nucleus, GABA g-aminobutyric acid, GLP-1/2 glucagon-like peptide 1/2, IL-6
interleukin-6, LHA lateral hypothalamus, LPB lateral parabrachial nucleus, NA noradrenalin,
NTS nucleus of the solitary tract, OXY oxytocin, PVN paraventricular nucleus, PP pancreatic
polypeptide, POMC pro-opiomelanocortin, TNF-a tumor necrosis factor alpha, TRH thyrotropin-
releasing hormone, VMN ventromedial nucleus. + indicates orexigenic effect; −, anorexigenic
effect; ?, unknown effect.
1.2.1. The Arcuate Nucleus
The arcuate nucleus (ARC), one of the hypothalamic nuclei, is thought to play a
pivotal role in the integration of signals regulating appetite. This is because the imme-
diate surroundings of the ARC are not being shielded by the blood–brain barrier and
this allows unrestricted access to afferent inputs (8).
Neuropeptide Y and pro-opiomelanocortin neurons in the hypothalamic ARC are proto-
typic metabolic sensors. Both use glucose as a signaling molecule, and both have receptors
for peripheral hormones, including insulin and leptin (8). The pro-opiomelanocortin neurons
produce a-melanocyte-stimulating hormone whose release and binding to melanocortin-3
and -4 receptors in the PVN and lateral hypothalamus reduces food intake and increases
EE mainly through projections from these nuclei to autonomic and neuroendocrine
80 Kelesidis, Kelesidis, Mantzoros
effector systems (9). Firing of NPY neurons releases both NPY and AgRP; NPY (10)
is an anabolic peptide that strongly stimulates ingestive behaviors and minimizes EE,
whereas AgRP acts as a functional antagonist of catabolic melanocortin receptors. Under
homeostatic conditions, leptin and insulin levels reflect the amount of adiposity in the
body(7,11). In addition to input from insulin and leptin, the ARC also senses changes in
energy balance conveyed by the gastric/gastrointestinal-system-secreted hormone ghrelin
(12) and the intestinal hormone peptide YY 3–36 (PYY 3–36) (13). By activating its
receptor on NPY/AgRP neurons, ghrelin stimulates food intake; currently ghrelin is the
only known circulating hormone to exert an orexigenic effect (14).
1.2.2. Paraventricular Nucleus
The other main hypothalamic areas identified as effectors of peripheral information
are the paraventricular nucleus (PVN), the lateral hypothalamus perifornical area, and
the ventromedial and dorsomedial nuclei (15,16). These structures are divided into two
categories. The lateral area constitutes the orexigenic limb, whereas the ventromedial,
dorsomedial, and paraventricular nuclei constitute the anorexigenic part of the hypotha-
lamus. The PVN, located adjacent to the third ventricle, acts to integrate neuropeptide
signals from numerous CNS regions, including the ARC and brain stem (17). The PVN
plays a major role in integration of all signaling functions that regulate energy home-
ostasis (18,19). This brain area seems to house neurons that mainly promote negative
energy balance and play an important role in energy homeostasis, at least in part, by
conveying input from the ARC to other key brain areas (20). Certainly more research is
needed to fully elucidate the role PVN plays in energy homeostasis.
1.2.3. Dorsomedial Nucleus/Hypothalamus
The dorsomedial nucleus (DMN) plays a significant role in the modulation of energy
intake. Destruction of the DMN results in hyperphagia and obesity, although less dra-
matic than in response to VMN lesioning. Injection of orexigenic peptides, NPY, galanin,
and GABA, into the DMN increases food intake (21), Similar to all other nuclei impor-
tant in energy regulation, the DMN has extensive connections with other hypothalamic
nuclei. It receives projections from AgRP/NPY neurons from the ARC but also contains
NPY-expressing cell bodies. Administration of melanocortin agonists in the DMN has
been shown to reduce both local NPY expression and suckling-induced hyperphagia in
rats most likely because of proximal localization of a-MSH immunoreactive fibers to
these NPY-expressing cells (22).
1.2.4. Lateral Hypothalamic Area and Perifornical Area
The lateral hypothalamic area and perifornical area (LHA/PFA) are other hypotha-
lamic areas involved in energy homeostasis. The PFA seems to be one of the most sensi-
tive areas for NPY-induced feeding, apparently more so than the PVN (15). The LHA/
PFA contains melanin-concentrating hormone (MCH) expressing neurons (16), and
among the key LHA neurons involved in body weight regulation are those that express
either orexin (23) or MCH (24). Data from animal studies support an important role
for MCH because targeted deletion of MCH (25) or its receptor (26) causes a weight-
reduced, lean, hypermetabolic phenotype whereas central administration (24) and/or
transgenic overexpression of this peptide increases food intake (22,24). The LHA/PFA
also contains neurons expressing prepro-orexin and releasing the peptide products orexin
Chapter 4 / Central Integration of Environmental and Endogenous Signals 81
A and B (also called hypocretins 1 and 2) (3,23). Orexin neurons project widely through
the CNS to several areas, including the PVN, ARC, nucleus tractus solitarius (NTS),
and dorsal motor nucleus of the vagus (27), i.e., to areas associated with arousal and
attention as well as feeding. The mechanisms by which the MCH and orexin neurons in
the LHA integrate CNS and peripheral signals to influence energy homeostasis remain
to be fully clarified (3). However, major targets are currently considered the endocrine
and autonomic nervous system, the cranial nerve motor nuclei, and cortical structures.
Finally, neurons in the LHA (mainly orexin-containing) may play an important role in
narcolepsy (28) and arguably an important role, by extension, in sleep regulation.
1.2.5. Ventromedial Hypothalamus
The ventromedial hypothalamus (VMH) has been known for many years to play a
role in energy homeostasis. The VMH receives NPY, AgRP, and a-MSH immunoreac-
tive projections from neurons in the ARC, and in turn, VMH neurons project onto both
hypothalamic nuclei (e.g., dorsomedial hypothalamus) and brain stem regions (e.g.,
NTS). Brain-derived neurotrophic factor (BDNF), a neurotrophic factor that has recently
been linked to weight loss (29), is highly expressed in the VMH, and its expression is
regulated both by food deprivation and melanocortin agonists (29). Mice with reduced
BDNF receptor expression or reduced BDNF signaling have increased food intake and
body weight (29). Therefore, BDNF neurons in the VMH may act as an additional down-
stream pathway through which nutritional status and the melanocortin system modulate
energy homeostasis. Finally, data from recent studies (30) strongly support the view that
BDNF plays a role as an anorexigenic factor in the dorsal vagal complex.
1.2.6. Brainstem/Nucleus Tractus Solitarius
The brain stem seems to play an important role in signal integration of energy avail-
ability (3). Caudal brainstem includes several sensors of nutrient intake and expenditure,
as well as receptors of peripheral hormones, including leptin and insulin (3). Extensive
reciprocal connections exist between the hypothalamus and brain stem, particularly the
NTS. The NTS is in close anatomical proximity to the area postrema, a circumven-
tricular organ with an incomplete blood–brain barrier (3). Like the ARC, the NTS is
therefore in an ideal position to respond to peripheral circulating signals, but in addition,
it also receives vagal afferents from the gastrointestinal tract and afferents from the glos-
sopharyngeal nerves (31). In addition to glucagon-like peptide 1 (GLP-1) (see below),
NPY neurons from the brain stem project forward to the PVN, and extracellular NPY
levels within the NTS are modulated by feeding (32). Other important structures found
in the NTS include NPY-binding sites (Y1 and Y5 receptors), melanocortin system (33),
and MC4R (3).
1.3. Synaptic Plasticity in Energy Balance Regulation
Recently, the scientific community realized that the system involving hypothalamic
neuropeptide systems is far from being static. There is a rapid synaptic remodeling (34),
and according to recent studies (34), changing metabolic states can cause alterations
in neuronal interactions by changes of the wiring of synapses and hypothalamic meta-
bolic circuits. In these studies, fasting resulted in a balance of stimulatory and inhibitory
synapses on orexin and NPY neurons that favored increasing activity of these neurons.
On the other hand, inhibitory interneurons of the same regions (neurons that would
82 Kelesidis, Kelesidis, Mantzoros
inhibit either orexin or NPY neuronal activity) exhibited a synaptic balance during fast-
ing that would support neuronal inactivation, thereby further enhancing the activity level
of orexin and NPY perikarya. These observations raise the notion that metabolic signals,
leptin in particular, may have an acute effect on synaptic plasticity within the appetite
centers. Recent data suggest that leptin-mediated plasticity in the ob/ob hypothalamus
may underlie some of the hormone’s behavioral effects (34). Similarly, the effects of
an orexigenic hormone, ghrelin, and anorexigenic hormone, estradiol, have also been
studied. It appears that synaptic plasticity is not leptin-specific since rearrangement
of synapses has also been observed in response to ghrelin and estradiol in a leptin-inde-
pendent manner (34). These observations raised the intriguing possibility that altered
synaptic plasticity could be an important way through which peripheral metabolic hor-
mones may influence brain functions in the long term.
1.4. Central Neuropeptides Regulating Energy Balance
The CNS structures responsible for regulating energy homeostasis mediate their
effects through the release of specific neuropeptides which, although grouped into orex-
igenic and anorexigenic subcategories, act in a coordinated manner, either synergis-
tically or antagonistically (summarized in Table 1). Several orexigenic neuropeptides
have been identified, which are expressed centrally and integrate peripheral signals to
reduce EE and/or increase energy intake, the most important being NPY, agouti-related
protein (AgRP), MCH, orexin, and galanin (GAL). On the other hand, signals of a posi-
tive energy balance are integrated centrally via anorexigenc neuropeptides, including
a-melanocyte-stimulating hormone (a-MSH), cocaine- and amphetamine-regulated
transcript, galanin-like peptide, the corticotrophin-releasing hormone family of pep-
tides, serotonin, and dopamine. The above peptides are presented briefly in Table 1.
1.5. Other Systems
1.5.1. Glucagon-Like Peptide 1
The NTS contains NPY, melanocortin, and GLP-1 neuronal circuits. GLP-1 forms the
major brain stem circuit known to regulate energy homeostasis. In the CNS, GLP-1 is syn-
thesized exclusively in the caudal NTS, and these preproglucagon neurons also express
leptin receptors. GLP1 immunoreactive fibers then project widely, but particularly to
the PVN and DMN, with fewer projections to the ARC. GLP-1 receptor expression is
also widespread, both within the hypothalamus (PVN, dorsomedial hypothalamus, and
supraoptic nucleus) and in the brain stem. Central administration of GLP-1, either into
the third or fourth ventricle, potently reduces fasting and NPY-induced food intake (35).
These data have suggested a role of not only circulating but also endogenous hypotha-
lamic GLP-1 in energy homeostasis.
1.5.2. Opioids
The opioid system appears to play a significant role in energy homeostasis. Release
of opioids, such as endorphins, during food intake could enhance the pleasure of eat-
ing. Opioids released in response to ingestion of sweet and other palatable foods can
increase central opioidergic activity and exogenously administered opioids generally
increase food intake (36). Microinjection of opioid agonists into the nucleus accumbens,
an important part of the reward circuit, stimulates the preferential consumption of highly
Table 1
Centrally expressed neuropeptides important in energy homeostasis
Factors that
Factors that upregulate downregulate
Peptide Receptors Expression Area expression expression Function
Orexigenic neuropeptides
Neuropeptide Y Six known NPY Expressed throughout the A state of negative energy Positive energy NPY is the most potent orexigen known,
(NPY) (138) (139, receptors (main CNS, but especially in balance (142) balance, associated and repeated third ventricle or PVN
140) are NPY1 and hypothalamic nuclei Ghrelin, increases the with increased leptin injection of NPY causes marked
NPY5 receptors) and the locus ceruleus expression of NPY and and insulin levels hyperphagia and obesity
(141) of the brainstem AgRP in the arcuate (152) Central administration of NPY increases
Co-localized with nucleus (14) PYY inhibits NPY food intake, decreases energy
agouti related protein Corticosterone (CORT) expression in the expenditure, decreases sympathetic
(AgRP) in the arcuate (143–146) arcuate nucleus via outflow to brown adipose tissue, and
nucleus Hypoglycemia the Y2-receptor (13) increases lipogenesis (139, 153)
(147–149) NPY stimulates basal plasma insulin and
morning plasma cortisol (54), effects
which are independent of increased
food intake
Agouti-related protein Mediates its Co-expressed with NPY Increased Ghrelin and Rising leptin and Central administration of AgRP in rodents
(AgRP) effects mainly in the arcuate nucleus CORT levels (10, 156, insulin levels increases feeding and body weight
by blocking (139,154,155) 157) (10, 156, 157) (159,160)
a-MSH from Declining carbohydrate AgRP also affects energy expenditure and
binding to stores and thermogenesis via the TRH system, such
MC4R and hypoglycaemia that exogenous AgRP in rats results in a
MC3R in the AgRP and NPY decreased TSH and total T4 simulating
brain (139) potentiate each other’s the hypothyroid state present during
effect on feeding fasting (161)
behavior (158) Activation of ARC NPY/AgRP neurons
potently stimulates feeding via a number
of pathways: the orexigenic effect of
NPY released in the PVN, AgRP
(continued)
Table 1
(continued)
Factors that
Factors that upregulate downregulate
Peptide Receptors Expression Area expression expression Function
antagonism of MC3R/MC4R in the
PVN, and local release of NPY and
GABA within the ARC to inhibit the
arcuate POMC neurons via Y1 and
GABA receptors, respectively
Melanin- Melanin Lateral hypothalamus Fasting Rising leptin levels Central administration of MCH causes
concentrating Concentrating (LHA) and the zona Insulin(163) hyperphagia (24)
hormone (MCH) Hormone incerta Declining fatty acid MCH knockout mice have reduced
Receptor 1 levels(164,165) weight and are lean due to hypophagia
(MCH1-R) and Ghrelin and glucose (139), and possibly increased energy
2 (MCH2-R) do not influence expenditure (162)
(139,162) its expression to a Mice with targeted disruption of
significant extent (166) MCH1-R display excessive feeding,
hyperactivity, increased metabolic rate,
and resistance to diet induced obesity
(25). This resistance to weight gain in
the setting of hyperphagia suggests that
MCH may promote a positive energy
balance mainly by decreasing activity
and energy expenditure, rather than by
increasing nutrient intake
Orexins (also known Orexin A has Lateral hypothalamus Similar to NPY and AgRP, Central orexin neurons express both
as hypocretins) high affinity and perifornical area they are stimulated neuropeptide (mainly NPY) receptors
Orexin A Orexin B for the orexin-1 orexin neurons by a negative energy and leptin receptors and hence may be
receptor, which project widely through balance and by rising able to integrate actions of both CNS
is highly the CNS levels of and peripheral signals
Major targets of these
expressed in the to areas including the glucocorticoids and neuropeptides are currently considered
VMH. Orexins PVN, ARC, NTS, and Ghrelin (23,158, the endocrine and autonomic nervous
A and B have dorsal motor nucleus 167–171) system, the cranial nerve motor nuclei,
equal affinities of the vagus and to Hypoglycaemia and and cortical structures
for the orexin-2 areas associated with insulin also exert a The considerable rise in orexin mRNA
receptor, which arousal and attention stimulatory effect observed in response to declining
is expressed as well as feeding on the expression blood sugar and the subsequent
primarily within of orexin mRNA stimulating effects of orexins on
the PVN (172,173) locomotor activity and searching
Leptin does not behavior suggests a
significantly role in hypothalamic arousal
regulate orexin (167, 172, 178–180)
levels, with obesity
and hyperphagia
(hyperleptinemic
states) actually being
associated with
increased levels of
these neuropeptides
(167, 174–177)
Galanin (GAL) GALR1, GALR2 Hypothalamus, primarily High-fat diets Exogenous administration of GAL
(181–184) in the PVN and ARC (185–187) stimulates feeding behavior,
nuclei, as well as the Declining glucose levels decreases energy expenditure and
LHA and perifornical fail to elicit changes in decreases sympathetic nervous system
area (181) GAL mRNA activity (189)
expression (188) GAL has a role in regulating
carbohydrate metabolism in the setting
of a high-fat diet (190)
(continued)
Table 1
(continued)
Factors that
Factors that upregulate downregulate
Peptide Receptors Expression Area expression expression Function
Anorexigenic peptides
Melanocortins are G-protein-coupled MC3R, expressed in Peripheral signals of Decrease of energy intake and increase of
cleaved from receptors (MCR) many areas of the energy abundance, energy expenditure (197)
proopiomelanocortin are expressed CNS and in several such as insulin and MC4R knockout mice are obese
(POMC): throughout the peripheral sites, and leptin (11, 193) MC4R antagonists administered centrally
a-melanocyte body MC4R, expressed In contrast to the decrease food intake dramatically (191)
stimulating mostly in the CNS orexigenic peptides, MC3R knockout mice have reduced
hormone (a-MSH) (192), are the receptors dietary nutrients exert lean body mass and increased fat
g-MSH (191) most relevant to no regulatory control mass, despite hypophagia and normal
energy regulation. Five over POMC expression metabolic rates (198)
melanocortin receptors (194–196) Central administration of MC4R
have been identified, agonists suppresses food intake, while
MC1R-MC5R, administration of antagonists results in
however, MC3R and hyperphagia
MC4R are most likely Furthermore, several MC4R mutations
to play a role in energy have been identified in obese
homeostasis. humans (199, 200), accounting for
approximately 5% of morbid obesity in
children (46, 201), (201)
Melanocortin agonists reduce both food
intake and body weight in several
mouse models of obesity (197, 202),
and their role in humans is being
evaluated in ongoing trials
Cocaine and No specific Arcuate nucleus, lateral Elevated levels of Food deprivation Direct intracerebroventricular CART
amphetamine receptor has hypothalamus and leptin, insulin and administration decreases nocturnal, as
regulated transcript been identified paraventricular nuclei glucocorticoids (204) well as fasting induced food intake in
(CART) to date (203) High-fat diets also exert rodents (139)
a stimulatory effect Neurons synthesizing CART are
on CART mRNA indirectly responsible for the effects
expression of leptin through sympathetic nervous
system activation (205)
CART may also act as a modulator of
the rebound thermogenic effect taking
place in states of hypothermia
(206, 207)
Galanin-like peptide GALR2 (208) Arcuate nucleus GALP mRNA levels Central injection of this hormone results
(GALP) increase in response in decreased feeding and body weight
to leptin and food (211)
restriction (209) Additionally, a thermogenic response
Glucose administration has been observed following acute
has been shown to administration of GALP (212)
increase GALP entry
into the brain (210)
Corticotropin CRF receptor PVN (CRF) CRF mRNA expression The CRH family of peptides: they
Releasing Hormone is tightly controlled by promote negative energy balance, they
(CRH) family of CORT levels continue to maintain tight glycemic
peptides: (214, 215) control through the effects of adrenal
Corticotropin steroids. (216–221)
Releasing Factor CRF regulates ACTH release from the
(CRF) anterior pituitary and subsequent
Endogenous CRF release of CORT from the adrenal
receptor ligands, glands (220, 222)
the urocortins (213)
(continued)
Table 1
(continued)
Factors that
Factors that upregulate downregulate
Peptide Receptors Expression Area expression expression Function
Interventional studies have demonstrated
that central administration of CRF
results in hypophagia, increased energy
expenditure, increased blood glucose,
and decreased insulin secretion
Serotonin (5-HT) Important anorexigenic role by mediating
leptin’s weight reducing effect (223)
and by stimulating POMC neurons to
release a-MSH (224)
5-HT2C receptor knockout mice have
decreased oxygen consumption,
increased food intake and increased
body weight (223). Several anti-obesity
drugs act by increasing 5-HT receptor
signaling
Increasing the availability of 5-HT by
affecting its release and reuptake in the
synaptic cleft, or the direct activation
of the 5-HT receptors, reduces food
consumption, whereas decreasing
5-HT receptor activation produces the
opposite effect
Arena Pharmaceuticals is currently
developing APD356, a new selective
5–HT2C receptor agonist for obesity.
Also in development is Wyeth’s
5–HT2C agonist WAY–16390915
Catecholamines Central a1 or Activation of 1 and, 2-adrenergic
b2 adrenergic receptors inhibits food intake
(b–ARs) Beta-adrenergic receptors are considered
receptors the most important receptors in the
adrenergic family for regulation
of energy expenditure in response
to dietary excess. Ablation of all
three b-Rs in mice results in obesity,
which is largely due to lower energy
expenditure, and this effect is enhanced
when mice are challenged with caloric
excess (48). Thus, these mice are
mildly obese on a regular diet but
become massively obese on a high fat
diet. These data are further supported
by the fact that mutations of b-Rs are
clearly associated with human obesity
Dopamine (DA) Dopamine receptor Tyrosine hydroxylase Plays a central role in energy intake,
isoforms (D1–D5) gene replacement, as seen in the abnormal feeding
and hence dopamine associated with pharmacological
replacement, into depletion and / or genetic disruption of
the caudate puta- dopamine synthesis (223)
men restores feeding, Striatal extracellular DA increases with
while gene therapy food intake in normal weight subjects
into either the caudate (225), but in obese subjects there is
putamen or nucleus reduced brain DA activity, which
accumbens (NAc) may predispose them to excessive
restores preference for food intake (225). Further studies are
a palatable diet needed to define the specific dopamine
receptor isoforms (D1–D5) that will
have the most significant weight
reducing effects, while avoiding
behavioral side effects or addiction
90 Kelesidis, Kelesidis, Mantzoros
palatable sucrose and fat (37). Conversely, opioid antagonists administered into the
nucleus accumbens reduce preferentially sucrose ingestion in comparison to other less
palatable substances (37). Several studies indicate that there are interactions of opioids
with other appetite-regulating processes (38).
1.5.3. The Cannabinoid System
Among the several novel antiobesity strategies currently under development, it was
hoped that pharmacological antagonism of the anabolic cannabinoid-1 receptor could
potentially be the first to come into clinical use. The cloning of the G-protein-coupled
cannabinoid-1 receptor (CB1R) provided valuable information about the mechanisms of
action of the principal active constituent of cannabis, d9-tetrahydrocannabinol (39). The
lipids anandamide and 2-arachidonoyl glycerol, which are known as endocannabinoids,
are natural ligands for CB1R. CB1R mediates the anabolic effects of exogenous and
endogenous cannabinoids (40). Anabolic and prodiabetic actions of endocannabinoids
include the following: (1) in the hypothalamus, increase of orexigenic and decrease of
anorexigenic neuropeptides; (2) in mesolimbic reward centers, enhancement of food
palatability and reward reinforcement; (3) in the hindbrain, blunting of nausea and
GI satiation signals transmitted from the vagus nerve; (4) in the GI tract, inhibition of
satiation signals and potentiation of hunger signals transmitted to vagal sensory nerve
terminals, as well as facilitation of nutrient absorption; (5) in adipose tissue and liver,
stimulation of lipogenesis; and (6) in muscle, impairment of glucose uptake (40).
Given the major anabolic actions of CB1R, it is not surprising that pharmacological
antagonism of this receptor promotes weight loss. A specific CB1R antagonist,
rimonabant, was created only a few years after the receptor was discovered and was
followed by the discovery of other antagonists such as taranabant. Through its actions in
the hypothalamus, hindbrain, mesolimbic reward centers, and vagus nerve, rimonabant
enhances anorexia, potentiates satiation signals, and lessens the motivation to consume
palatable, rewarding foods. Together, these effects reduce food intake and body weight.
Beneficial effects of rimonabant on body weight, adiposity, and other features of the
metabolic syndrome have been confirmed in phase III human trials lasting up to 2 years
(41–43) which led many European nations to approve this agent as a new drug for obesity.
The approval in the USA has been delayed, however, owing to concerns about a potential
for psychiatric side effects. It remains to be seen whether rimonabant or taranabant or
both will eventually be approved for obesity and the metabolic syndrome.
2. ENERGY EXPENDITURE IN ENERGY HOMEOSTASIS
According to the first law of thermodynamics, the total energy of a system plus the
surroundings remains constant. Obesity can result, therefore, from a relative increase in
energy intake (food) compared to EE. The regulation of EE and its role in body weight
homeostasis has not been very well studied to date. Potent physiologic mechanisms
maintain body weight within a narrow “set point” and regulate energy balance with
accuracy in most humans (44), as demonstrated by under- and overfeeding studies
(45). Certain thermogenic mechanisms, such as leptin-induced increases in EE (46,47)
and diet-induced thermogenesis, a critically important antiobesity mechanism as per
studies in rodents (48,49), have evolved in mammals to allow burning up of excess
Chapter 4 / Central Integration of Environmental and Endogenous Signals 91
energy (50,51). Human studies suggest that increased sympathetic nervous system
(SNS) activity, decreased parasympathetic nervous system activity, and an inferred
form of physical activity known as non-exercise activity thermogenesis (NEAT)
lead to an increase in EE in overfeeding states and obesity (52–55). However, many
more studies are needed to determine the importance of thermogenic, antiobesity
mechanisms in humans (48).
2.1. Components of Energy Expenditure
EE can be categorized into obligatory (basal) and adaptive (facultative) thermogenesis.
Obligatory EE includes all processes that are involved in the maintenance of basic meta-
bolic and physiologic processes, including the maintenance of ion gradients, muscle tone,
digestion, and blood flow (standard metabolic rate). Adaptive thermogenesis includes
cold and diet-induced thermogenesis. For example, although thyroid hormone (TH) is
required for up to 30% of standard metabolic rate, adaptive increases in TH are required
for normal cold-induced thermogenesis (56). Physical activity can also have long-lasting
effects on resting metabolic rate (57). Approximate contributions of the various EE
components are resting metabolic rate (70%), physical activity (20%), facultative (10%),
with physical activity representing the most variable component (58).
2.2. The Role of Regulation of Energy Expenditure
in the Development of Obesity
Mammals have potent homeostatic mechanisms, which maintain body weight by
changing food intake and EE (59). Only relative differences in EE might explain
predisposition to obesity since obese patients have increased EE when compared to lean
subjects (56). Although there are data demonstrating that increased food intake causes
obesity, there has been less evidence that decreased EE may specifically lead to obesity.
Differences in EE have been proposed to be associated with the development of obesity
over a period of years (60) while genetic factors may play a major role in controlling
EE (52,61). However, other reports do not support the hypothesis that abnormal regulation
of EE leads to obesity (58,62,63). For example, several studies have failed to find obesity-
promoting mechanisms to explain differences between lean and obese subjects, including
SNS nerve activity (64), catecholamine turnover (65), lipolysis (66), the thermic effect
of food, (58) and THs (67). In summary, the hypothesis that relatively low EE contributes
to the development of obesity has been supported by a few but not all studies. It remains
unclear whether stimulation of EE in humans will eventually prove to be a useful
approach for antiobesity therapy.
2.3. Regulation of Energy Expenditure
Regulation of EE depends on many factors, including physical activity, changes in
energy intake/diet, THs, SNS, adrenergic receptors, futile cycles, and intermediary
metabolism genes.
2.3.1. Physical Activity
Increasing physical activity represents an effective method to resist obesity in the
setting of increased food intake; it has effects on EE both acutely, with large increases in
maximal oxygen consumption, and chronically via increased mitochondrial proliferation
92 Kelesidis, Kelesidis, Mantzoros
(68). In humans, a combination of decreased food intake and physical activity is most
successful for sustained weight loss (69). Overfeeding studies in lean humans showed that
the majority of increased EE in response to caloric excess occurs via increased non-exercise
activity thermogenesis (NEAT), a separate category of physical activity that is related to
adiposity which includes all tasks of daily living (70), and not via increases in thermic
effect of food, or coordinated physical activity (55). Further research into the regulation of
physical activity as a specific mechanism to control body fat stores is still needed.
Although there are limited data available based on measurements of everyday,
real life physical activity at the population level, it appears that energy intake has
increased and physical activity has decreased more than enough to explain the increasing
prevalence of obesity in the population (71). A related controversial issue in the area
is how much physical activity should be recommended for prevention of weight gain,
for weight loss, and/or for prevention of weight regain after weight loss. In this respect,
several studies have shown that very large increases in physical activity are necessary
to avoid weight regain after weight loss (72) while very small increases may prevent
weight gain (59).
2.3.2. Changes in Energy Intake/Diet
Diet composition
The role of diet composition on body weight is an area of controversy in the field
of obesity research. Diet composition can affect body weight in individuals who are in
energy balance. In a recent review, Astrup et al. (73) found that body weight is reduced
slightly as dietary fat content of the diet is lowered in individuals who were in energy
balance. Reducing dietary fat without food restriction may affect both energy intake
and EE in small ways, since voluntary intake may be lower with low- vs. high-fat diets
(74,75). Increasing dietary carbohydrate and reducing dietary fat could also be expected
to produce a slight increase in the thermic effect of food (75), since carbohydrate produces
more thermic effect than fat does, but this remains to be conclusively shown. The impact
of high- vs. low-glycemic diets as well as of protein diets on energy balance is still the
focus of intensive research efforts (76,77).
Diet composition during negative energy balance
Diet composition may have different effects depending on whether subjects are
in energy balance or whether they are in positive or negative energy balance. During
equivalent negative energy balance, there might be little difference in altering the fat/
carbohydrate ratio of the diet and there seems to be similar body weight and body fat
loss with high- and low-fat diets when total energy intake is fixed at a level below energy
requirements (78). However, there are several reports of differences in weight loss with
high- and low-fat diets when energy intake is not fixed (79,80), suggesting that diet
composition may affect satiety or hunger during dieting. A recent meta-analysis (81)
concluded that nonenergy-restricted, low-carbohydrate diets were at least as effective as
low-fat diets over a period of 1 year. Lowering dietary fat has little impact during negative
energy balance. Therefore, in general, low-fat diets have not been found to lead to greater
weight loss than diets higher in fat content.
Diet composition during positive energy balance
During positive energy balance, diet composition can have a relatively larger effect
on energy balance. Studies have shown that excess energy is efficiently stored in the
Chapter 4 / Central Integration of Environmental and Endogenous Signals 93
body regardless of its source, but it has been proposed that excess energy from dietary
fat is stored more efficiently than excess energy from carbohydrates (82). This area is of
significant interest and the focus of intensive research efforts.
2.3.3. Thyroid Hormones
Thyroid hormones (TH; including T4 and T3) play a significant role in regulating EE.
Thyroid hormones mediate ~30% of basal thermogenesis and stimulate numerous
anabolic and catabolic pathways (reviewed in (83)). Low TH levels in response to dietary
restriction are associated with reduced EE during weight loss and act to resist body
weight change in obesity (84). These changes in TH levels are also associated with
changes in EE and SNS. All these alterations are to a certain degree due to falling leptin
levels in response to weight loss (84), but the extent to which falling leptin mediates the
alterations in TH in response to food deprivation and whether leptin administration in
replacement doses would improve weight loss maintenance remain to be seen.
2.3.4. Sympathetic Nervous System and Adrenergic Receptors
The SNS is another significant regulator of EE (reviewed in (85)). b-Adrenergic
receptors (AR) are apparently the most important receptors in the adrenergic family
for regulation of EE in response to dietary excess but other receptors are also important
in EE regulation (86). Several studies support the model of altered EE in response to
caloric excess, and resistance to obesity. In most rodent models of obesity there is low
SNS activity, which can be associated with propensity for future weight gain (85,87),
and activation of this pathway by b-AR agonists is effective in reducing obesity in mice
(88,89). Numerous attempts to alter SNS function (by surgical, chemical, immunological,
and genetic means) failed to affect body weight, however, and thus the importance of
SNS-mediated diet-induced thermogenesis lacks support (90–92). On the other hand,
ablation of all 3 b-ARs in mice (b-less mice) results in obesity that is entirely due to
lower EE, and this deficit is enhanced when mice are challenged with caloric excess
(48). These results are supported by genetic studies in humans reporting mutations in
b-ARs that are associated with human obesity (86,93). In contrast, the development of
b-AR agonists for the treatment of obesity has failed to result in any usable compounds
in studies in humans.
2.3.5. Futile Cycles
EE in mammals can be regulated by thermogenic futile cycles that can involve various
metabolic pathways, including the glycolysis pathway (94), as well as calcium (95–97),
sodium, and proton cycling in cells. Although lipogenic/lipolytic futile cycles are stimulated
in white adipose tissue (WAT) in response to peroxisome proliferator-activated receptor
(PPAR) agonists (98), futile cycles have not yet been shown to play a significant role in
mammalian body weight regulation, however.
2.3.6. Intermediary Metabolism Genes that Regulate EE
and Body Weight
There is increasing evidence that EE in mammals is controlled at numerous, rate-
limiting, and, in some cases, leptin-mediated steps in glucose and fatty acid metabolism.
In many rodent models loss of function of key synthetic enzymatic steps in fatty acid
synthesis results in increased EE, reduced body weight, and obesity resistance (99–102).
In humans, polymorphisms in the rate-limiting enzyme for triglyceride synthesis are
94 Kelesidis, Kelesidis, Mantzoros
associated with lean kindreds (103). AMP kinase, which is regulated by leptin, is an
emerging, central mediator of these critical steps in fatty acid metabolism and affects
appetite and EE (104,105).
2.4. Thermogenic Tissues
Many tissues have the metabolic potential to mediate thermogenesis as a specific
response to increased body weight and adipose stores.
2.4.1. Brown Adipose Tissue
Brown adipose tissue (BAT) plays a critical role in thermogenesis and body weight
regulation in rodents (106), but may not represent an attractive target for antiobesity
treatment because of its apparent absence in adult humans. BAT is a highly thermogenic
form of adipose tissue (107). Stimulation of b-ARs by catecholamines or synthetic b-AR
agonists markedly stimulates EE, primarily in BAT (50). b-AR agonists have not been
proven to be effective as potential treatment options for human obesity, because of low
abundance of the b3-AR in human tissues, or lack of specificity for the human b3-AR,
or intolerable side effects because of the high doses needed. These considerations have
made the use of b-AR agonists for human obesity uncertain (108). High fat feeding
also results in marked BAT hypertrophy and increased EE, suggesting that BAT plays a
role in resisting obesity (49,50). Subsequent isolation and cloning of a 32-kDa protein,
then-called thermogenin, initiated a search for the function of such proteins (uncoupling
proteins, or UCPs) that uncouple oxidative phosphorylation and thus have the capacity
to produce heat (109). Some studies (110,111) have supported a role for UCPs in more
specialized forms of thermogenesis, but other studies have revealed controversial results.
Others have emphasized the existence of a paradox: BAT is necessary for normal body
weight regulation, but the major thermogenic protein, UCP-1, is not apparently absolutely
required (112). This paradox may be solved by either finding another thermogenic
mediator in BAT or investigating other tissues as potential mediators of diet-induced
thermogenesis.
2.4.2. White Adipose Tissue
White adipose tissue (WAT) clearly participates actively in many metabolic processes
(113) via regulation of glucose uptake, lipolysis, response to adrenergic stimulation, and
release of numerous cytokines (leptin, ASP, adiponectin, resistin) (114). Furthermore,
although the metabolic rate of WAT is often cited as low, strong evidence indicates
that significant overall EE derives from WAT (115). Secreted WAT-specific cytokines,
including leptin, adiponectin, resistin, and other substances, are reviewed in previously
published papers (113). Our current understanding is that WAT can be viewed not only as
a storage depot, but as an important endocrine organ that profoundly affects EE and body
weight. WAT represents an important potential antiobesity target via increased EE.
2.5. Approaches to Treat Obesity via Manipulation of EE
Appropriate strategies for weight loss would be to either prevent positive energy
balance and stop the gradual weight gain of the population or treat obesity in those already
affected. This involves producing negative energy balance to produce weight loss, followed
by achieving energy balance permanently at a lowered body weight. In the following
paragraphs, we discuss the above approaches. The major antiobesity pathways that have
Chapter 4 / Central Integration of Environmental and Endogenous Signals 95
been targeted for manipulation of EE include mitochondrial uncoupling, the activation of
the SNS, and TH use. With the possible exception of the medicines discussed below, none
of these has been successful in treating human obesity because of either intolerable side
effects or lack of efficacy, as judged by prevention of further weight gain, 5–10% loss of
weight, metabolic improvement, and/or long-term maintenance (116).
2.5.1. Uncoupling Oxidative Phosphorylation
Compounds that short circuit the mitochondrial membrane potential, called uncouplers,
had preceded the isolation and characterization of endogenous UCPs. These compounds
(2,4-dinotrophenol, for example), which are effective treatments for obesity through
their ability to increase oxygen consumption, have been abandoned because of a narrow
therapeutic window and intolerable side effects (117).
2.5.2. Hormones
Leptin
Leptin is an adipocyte-derived cytokine that stimulates numerous pathways in the CNS,
including weight loss. Exogenously administered leptin results in decreased food intake
in leptin-deficient humans and, presumably via the SNS, in modest (if any) increase in
EE and fat mobilization. The majority of obese human patients have elevated leptin levels
in serum, however, indicating that there is resistance to leptin. The effect of exogenous
leptin on body weight loss in humans is highly variable across a wide patient population,
most likely because of already high leptin levels in obese patients reflecting a variable
degree of tolerance or resistance to its effects (118). Although leptin-deficient patients
respond markedly to leptin treatment, these patients are extremely rare (119). In addition,
it is possible that certain patients with partial leptin deficiency may also respond to exog-
enous leptin treatment (120,121), but this remains to be studied in the future.
Thyroid hormone
Activation of TH receptor b increases metabolic rate and causes weight loss in mice,
and thus may become a drug target for obesity (122). Subtype-specific compounds that
are selective for a single thyroid receptor isoform are potential approaches to making
antiobesity compounds (123), but this is currently only an emerging area of research.
2.5.3. Sympathomimetics
Ephedrine is a sympathomimetic agent that increases numerous SNS activity responses,
including heart rate, blood pressure, and basal metabolic rate, probably through direct
activation of adrenergic receptors. Its usefulness is limited by cardiovascular side effects
and relatively low efficacy in the treatment of obesity, although in combination with
caffeine it may show greater efficacy (124).
Sibutramine is a nonselective NE/serotonin reuptake inhibitor that acts both as an
appetite suppressant (125) and activator of SNS activity via the b3-AR (126). Sibutramine
is currently indicated for obesity treatment in the absence of known cardiovascular
disease (see relevant chapter below) (127). Dose-limiting toxicity and potential side
effects include increased heart rate and blood pressure. Patients should be screened for
evidence of underlying atherosclerotic heart disease and need to be followed periodically
while on sibutramine.
Nicotine stimulates norepinephrine release from sympathetic nerve terminals, resulting
in modest (5%) thermogenesis (128). Smoking cessation may have contributed to the
96 Kelesidis, Kelesidis, Mantzoros
increase in the prevalence of obesity because of withdrawal of nicotine, which acts as
both an appetite suppressant and stimulator of thermogenesis (129).
Caffeine stimulates thermogenesis by inhibition of adenosine receptors on tissues,
resulting in increased intracellular cAMP levels and lipolysis (130). Caffeine may be
useful, to a small extent, as a treatment for obesity, especially in combination with other
compounds such as ephedrine or nicotine (128), and long-term studies have shown ben-
eficial effects of endogenous insulin sensitizers, including adiponectin, on the metabolic
syndrome and diabetes. Caffeine intake is not currently included among the recommended
treatments for obesity, however.
The ability of b-AR agonists to reverse obesity in rodent models led to great hopes
that these could become effective treatments in humans (89). b3-Agonists, in particular,
would seem to be ideal targets for drug development, because their expression is restricted
to adipose tissue and they effectively reduce body weight in rodents (107). The potential
mechanisms of action of b-agonists are multiple, including increased mitochondrial
function and abundance, differentiation of BAT in WAT depots, lipolysis, and increased
fatty acid oxidation. However, the future of b-agonists as effective antiobesity treatments
remains unclear as outlined above (131,132).
2.5.4. Producing Negative Energy Balance and Weight Loss
Food restriction is practically the primary driver of weight loss in humans; any diet
that results in ingesting fewer calories will produce weight loss. Although it is also pos-
sible to lose weight with physical activity alone (133,134), it is difficult for most people
to exercise enough to achieve a degree of negative energy balance that would result in
significant weight loss. This is also why adding physical activity to food restriction pro-
duces only a minimal additional amount of weight loss (133,134). Unfortunately, weight
tends to be regained in most people regardless of the composition of the diet used for
weight loss (79,80). It has been estimated that long-term success in obesity treatment
is about 20% or less if success was defined as maintaining a 10% reduction in body
weight for at least 1 year (135). The mechanisms underlying the ability of the organism
to defend a given body weight are under intensive investigation.
2.5.5. Weight Loss Maintenance
Although there are several studies about factors that contribute to weight loss, we have
very little evidence to understand the factors that contribute to weight loss maintenance.
In a descriptive study by Klem et al. (72), although most (>90%) participants reported
that they used both food restriction and physical activity to lose weight, there was little
similarity in the types of diets used for weight loss (72). Conversely, in this study many
similarities were seen in the behaviors and strategies used to maintain weight loss. The
four that stand out are as follows:
• Eating a moderately low-fat, high-carbohydrate diet. This is consistent with previous work
suggesting that low-fat diets should be better than high-fat diets in preventing positive energy
balance (75).
• Consistent self-monitoring of body weight, food intake, and physical activity. This is consistent
with other reports that self-monitoring facilitates long-term success in weight management (136).
• Eating breakfast every day. This is consistent with a growing body of data showing that eating
breakfast facilitates maintenance of a healthy body weight (137).
• Very high levels of physical activity.
Chapter 4 / Central Integration of Environmental and Endogenous Signals 97
2.6. Therapeutic Implications/Future Directions
The exploding obesity pandemic certainly suggests that efficient and safe behavioral
and pharmacological approaches to treat obesity are needed. Efforts to clarify the mech-
anisms underlying energy homeostasis have provided a pathway for identifying and
studying targets for drug development in the treatment of obesity and related metabolic
disorders. As an example, identifying the mechanisms underlying neuronal resistance
to adiposity signals has clear therapeutic implications; drugs that prevent or reverse this
resistance can be predicted to favor the defence of a reduced level of body fat. A more
detailed understanding of the pathogenesis of human obesity hopefully will ultimately
guide the development of efficacious treatment options that could benefit the affected
individuals.
REFERENCES
1. Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM. Positional cloning of the mouse
obese gene and its human homologue. Nature 1994; 372(6505):425–432.
2. Barsh GS, Schwartz MW. Genetic approaches to studying energy balance: perception and integration.
Nat Rev Genet 2002; 3(8):589–600.
3. Horvath TL, Diano S, Tschop M. Brain circuits regulating energy homeostasis. Neuroscientist 2004;
10(3):235–246.
4. Kalra SP, Dube MG, Pu S, Xu B, Horvath TL, Kalra PS. Interacting appetite-regulating pathways in the
hypothalamic regulation of body weight. Endocr Rev 1999; 20(1):68–100.
5. Saper CB, Chou TC, Elmquist JK. The need to feed: homeostatic and hedonic control of eating. Neuron
2002; 36(2):199–211.
6. Berthoud HR. Multiple neural systems controlling food intake and body weight. Neurosci Biobehav
Rev 2002; 26(4):393–428.
7. Schwartz MW, Seeley RJ, Woods SC, Weigle DS, Campfield LA, Burn P et al. Leptin increases
hypothalamic pro-opiomelanocortin mRNA expression in the rostral arcuate nucleus. Diabetes 1997;
46(12):2119–2123.
8. Benoit SC, Air EL, Coolen LM, Strauss R, Jackman A, Clegg DJ et al. The catabolic action of insulin
in the brain is mediated by melanocortins. J Neurosci 2002; 22(20):9048–9052.
9. Fan W, Boston BA, Kesterson RA, Hruby VJ, Cone RD. Role of melanocortinergic neurons in feeding
and the agouti obesity syndrome. Nature 1997; 385(6612):165–168.
10. Hahn TM, Breininger JF, Baskin DG, Schwartz MW. Coexpression of AgRP and NPY in fasting-
activated hypothalamic neurons. Nat Neurosci 1998; 1(4):271–272.
11. Cowley MA, Smart JL, Rubinstein M, Cerdan MG, Diano S, Horvath TL et al. Leptin activates anorexigenic
POMC neurons through a neural network in the arcuate nucleus. Nature 2001; 411(6836):480–484.
12. Kojima M, Hosoda H, Date Y, Nakazato M, Matsuo H, Kangawa K. Ghrelin is a growth-hormone-
releasing acylated peptide from stomach. Nature 1999; 402(6762):656–660.
13. Batterham RL, Cowley MA, Small CJ, Herzog H, Cohen MA, Dakin CL et al. Gut hormone PYY(3–36)
physiologically inhibits food intake. Nature 2002; 4186898.:650–654.
14. Nakazato M, Murakami N, Date Y, Kojima M, Matsuo H, Kangawa K et al. A role for ghrelin in the
central regulation of feeding. Nature 2001; 409(6817):194–198.
15. Stanley BG, Magdalin W, Seirafi A, Thomas WJ, Leibowitz SF. The perifornical area: the major focus
of (a) patchily distributed hypothalamic neuropeptide Y-sensitive feeding system(s). Brain Res 1993;
604(1/2):304–317.
16. Marsh DJ, Weingarth DT, Novi DE, Chen HY, Trumbauer ME, Chen AS et al. Melanin-concentrating
hormone 1 receptor-deficient mice are lean, hyperactive, and hyperphagic and have altered metabolism.
Proc Natl Acad Sci USA 2002; 99(5):3240–3245.
17. Giraudo SQ, Billington CJ, Levine AS. Feeding effects of hypothalamic injection of melanocortin 4
receptor ligands. Brain Res 1998; 809(2):302–306.
98 Kelesidis, Kelesidis, Mantzoros
18. Fekete C, Legradi G, Mihaly E, Huang QH, Tatro JB, Rand WM et al. a-Melanocyte-stimulating hormone
is contained in nerve terminals innervating thyrotropin-releasing hormone-synthesizing neurons in the
hypothalamic paraventricular nucleus and prevents fasting-induced suppression of prothyrotropin-
releasing hormone gene expression. J Neurosci 2000; 20(4):1550–1558.
19. Sarkar S, Lechan RM. Central administration of neuropeptide Y reduces alpha-melanocyte-stimulating
hormone-induced cyclic adenosine 5¢-monophosphate response element binding protein (CREB)
phosphorylation in pro-thyrotropin-releasing hormone neurons and increases CREB phosphorylation
in corticotropin-releasing hormone neurons in the hypothalamic paraventricular nucleus. Endocrinology
2003; 144(1):281–291.
20. Tokunaga K, Fukushima M, Kemnitz JW, Bray GA. Comparison of ventromedial and paraventricular
lesions in rats that become obese. Am J Physiol 1986; 251(6 Pt 2):R1221–R1227.
21. Stanley BG, Daniel DR, Chin AS, Leibowitz SF. Paraventricular nucleus injections of peptide YY and
neuropeptide Y preferentially enhance carbohydrate ingestion. Peptides 1985; 6(6):1205–1211.
22. Chen P, Williams SM, Grove KL, Smith MS. Melanocortin 4 receptor-mediated hyperphagia and
activation of neuropeptide Y expression in the dorsomedial hypothalamus during lactation. J Neurosci
2004; 24(22):5091–5100.
23. Sakurai T, Amemiya A, Ishii M, Matsuzaki I, Chemelli RM, Tanaka H et al. Orexins and orexin receptors:
a family of hypothalamic neuropeptides and G protein-coupled receptors that regulate feeding behavior.
Cell 1998; 92(5):1.
24. Qu D, Ludwig DS, Gammeltoft S, Piper M, Pelleymounter MA, Cullen MJ et al. A role for melanin-
concentrating hormone in the central regulation of feeding behaviour. Nature 1996; 380(6571):243–247.
25. Shimada M, Tritos NA, Lowell BB, Flier JS, Maratos-Flier E. Mice lacking melanin-concentrating
hormone are hypophagic and lean. Nature 1998; 396(6712):670–674.
26. Chen Y, Hu C, Hsu CK, Zhang Q, Bi C, Asnicar M et al. Targeted disruption of the melanin-concentrating
hormone receptor-1 results in hyperphagia and resistance to diet-induced obesity. Endocrinology 2002;
143(7):2469–2477.
27. de Lecea L, Kilduff TS, Peyron C, Gao X, Foye PE, Danielson PE et al. The hypocretins: hypothalamus-
specific peptides with neuroexcitatory activity. Proc Natl Acad Sci USA 1998; 95(1):322–327.
28. Williams CJ, Hu FB, Patel SR, Mantzoros CS. Sleep duration and snoring in relation to biomarkers of
cardiovascular disease risk among women with type 2 diabetes. Diabetes Care 2007; 30(5):1233–1240.
29. Xu B, Goulding EH, Zang K, Cepoi D, Cone RD, Jones KR et al. Brain-derived neurotrophic factor
regulates energy balance downstream of melanocortin-4 receptor. Nat Neurosci 2003; 6(7):736–742.
30. Bariohay B, Lebrun B, Moyse E, Jean A. Brain-derived neurotrophic factor plays a role as an anorexigenic
factor in the dorsal vagal complex. Endocrinology 2005; 146(12):5612–5620.
31. Kalia M, Sullivan JM. Brainstem projections of sensory and motor components of the vagus nerve in
the rat. J Comp Neurol 1982; 211(3):248–265.
32. Dumont Y, Fournier A, Quirion R. Expression and characterization of the neuropeptide Y Y5 receptor
subtype in the rat brain. J Neurosci 1998; 18(15):5565–5574.
33. Grauerholz BL, Jacobson JD, Handler MS, Millington WR. Detection of pro-opiomelanocortin mRNA
in human and rat caudal medulla by RT-PCR. Peptides 1998; 19(5):939–948.
34. Horvath TL. Synaptic plasticity in energy balance regulation. Obesity (Silver Spring) 2006; 14Suppl
5):228S–233S.
35. Yoshihara T, Honma S, Honma K. Effects of restricted daily feeding on neuropeptide Y release in the
rat paraventricular nucleus. Am J Physiol 1996; 2704 Pt 1):E589–E595.
36. Si EC, Bryant HU, Yim GK. Opioid and non-opioid components of insulin-induced feeding. Pharmacol
Biochem Behav 1986; 244):899–903.
37. Zhang M, Balmadrid C, Kelley AE. Nucleus accumbens opioid, GABaergic, and dopaminergic modulation
of palatable food motivation: contrasting effects revealed by a progressive ratio study in the rat. Behav
Neurosci 2003; 117(2):202–211.
38. Mercer ME, Holder MD. Food cravings, endogenous opioid peptides, and food intake: a review. Appetite
1997; 29(3):325–352.
39. Matsuda LA, Lolait SJ, Brownstein MJ, Young AC, Bonner TI. Structure of a cannabinoid receptor and
functional expression of the cloned cDNA. Nature 1990; 346(6284):561–564.
Chapter 4 / Central Integration of Environmental and Endogenous Signals 99
40. Pagotto U, Marsicano G, Cota D, Lutz B, Pasquali R. The emerging role of the endocannabinoid system
in endocrine regulation and energy balance. Endocr Rev 2006; 27(1):73–100.
41. Van Gaal LF, Rissanen AM, Scheen AJ, Ziegler O, Rossner S. Effects of the cannabinoid-1 receptor
blocker rimonabant on weight reduction and cardiovascular risk factors in overweight patients: 1-year
experience from the RIO-Europe study. Lancet 2005; 365(9468):1389–1397.
42. Pi-Sunyer FX, Aronne LJ, Heshmati HM, Devin J, Rosenstock J. Effect of rimonabant, a cannabinoid-1
receptor blocker, on weight and cardiometabolic risk factors in overweight or obese patients: RIO-
North America: a randomized controlled trial. JAMA 2006; 295(7):761–775.
43. Despres JP, Golay A, Sjostrom L. Effects of rimonabant on metabolic risk factors in overweight patients
with dyslipidemia. N Engl J Med 2005; 353(20):2121–2134.
44. Friedman JM. A war on obesity, not the obese. Science 2003; 299(5608):856–858.
45. Rosenbaum M, Leibel RL, Hirsch J. Obesity. N Engl J Med 1997; 337(6):396–407.
46. O’Rahilly S, Farooqi IS, Yeo GS, Challis BG. Minireview: human obesity-lessons from monogenic
disorders. Endocrinology 2003; 144(9):3757–3764.
47. Halaas JL, Boozer C, Blair-West J, Fidahusein N, Denton DA, Friedman JM. Physiological response to
long-term peripheral and central leptin infusion in lean and obese mice. Proc Natl Acad Sci USA 1997;
94(16):8878–8883.
48. Bachman ES, Dhillon H, Zhang CY, Cinti S, Bianco AC, Kobilka BK et al. betaAR signaling required
for diet-induced thermogenesis and obesity resistance. Science 2002; 297(5582):843–845.
49. Glick Z, Teague RJ, Bray GA. Brown adipose tissue: thermic response increased by a single low protein,
high carbohydrate meal. Science 1981; 213(4512):1125–1127.
50. Rothwell NJ, Stock MJ. A role for brown adipose tissue in diet-induced thermogenesis. Nature 1979;
281(5726):31–35.
51. Stock MJ. Gluttony and thermogenesis revisited. Int J Obes Relat Metab Disord 1999; 23(11):
1105–1117.
52. Bouchard C, Tremblay A, Despres JP, Nadeau A, Lupien PJ, Theriault G et al. The response to long-
term overfeeding in identical twins. N Engl J Med 1990; 322(21):1477–1482.
53. Stunkard AJ, Harris JR, Pedersen NL, McClearn GE. The body-mass index of twins who have been
reared apart. N Engl J Med 1990; 322(21):1483–1487.
54. Saad MF, Alger SA, Zurlo F, Young JB, Bogardus C, Ravussin E. Ethnic differences in sympathetic
nervous system-mediated energy expenditure. Am J Physiol 1991; 261(6 Pt 1):E789–E794.
55. Levine JA, Eberhardt NL, Jensen MD. Role of nonexercise activity thermogenesis in resistance to fat
gain in humans. Science 1999; 283(5399):212–214.
56. de Jesus LA, Carvalho SD, Ribeiro MO, Schneider M, Kim SW, Harney JW et al. The type 2
iodothyronine deiodinase is essential for adaptive thermogenesis in brown adipose tissue. J Clin Invest
2001; 108(9):1379–1385.
57. Speakman JR, Selman C. Physical activity and resting metabolic rate. Proc Nutr Soc 2003; 62(3):621–634.
58. Ravussin E, Swinburn BA. Pathophysiology of obesity. Lancet 1992; 340(8816):404–408.
59. Hill JO, Wyatt HR, Reed GW, Peters JC. Obesity and the environment: where do we go from here. Sci-
ence 2003; 299(5608):853–855.
60. Ravussin E, Lillioja S, Knowler WC, Christin L, Freymond D, Abbott WG et al. Reduced rate of energy
expenditure as a risk factor for body-weight gain. N Engl J Med 1988; 318(8):467–472.
61. Bogardus C, Lillioja S, Ravussin E, Abbott W, Zawadzki JK, Young A et al. Familial dependence of the
resting metabolic rate. N Engl J Med 1986; 315(2):96–100.
62. Weyer C, Pratley RE, Salbe AD, Bogardus C, Ravussin E, Tataranni PA. Energy expenditure, fat oxidation,
and body weight regulation: a study of metabolic adaptation to long-term weight change. J Clin Endocrinol
Metab 2000; 85(3):1087–1094.
64. Scherrer U, Randin D, Tappy L, Vollenweider P, Jequier E, Nicod P. Body fat and sympathetic nerve
activity in healthy subjects. Circulation 1994; 89(6):2634–2640.
65. Rumantir MS, Vaz M, Jennings GL, Collier G, Kaye DM, Seals DR et al. Neural mechanisms in human
obesity-related hypertension. J Hypertens 1999; 17(8):1125–1133.
66. Jansson PA, Larsson A, Smith U, Lonnroth P. Glycerol production in subcutaneous adipose tissue in
lean and obese humans. J Clin Invest 1992; 89(5):1610–1617.
100 Kelesidis, Kelesidis, Mantzoros
67. Kokkoris P, Pi-Sunyer FX. Obesity and endocrine disease. Endocrinol Metab Clin North Am 2003;
32(4):895–914.
68. Irrcher I, Adhihetty PJ, Joseph AM, Ljubicic V, Hood DA. Regulation of mitochondrial biogenesis in
muscle by endurance exercise. Sports Med 2003; 33(11):783–793.
69. Jakicic JM. Exercise in the treatment of obesity. Endocrinol Metab Clin North Am 2003; 32(4):967–980.
70. Levine J, Baukol P, Pavlidis I. The energy expended in chewing gum. N Engl J Med 1999;
341(27):2100.
71. Brown WJ, Williams L, Ford JH, Ball K, Dobson AJ. Identifying the energy gap: magnitude and deter-
minants of 5-year weight gain in midage women. Obes Res 2005; 13(8):1431–1441.
72. Klem ML, Wing RR, McGuire MT, Seagle HM, Hill JO. A descriptive study of individuals successful
at long-term maintenance of substantial weight loss. Am J Clin Nutr 1997; 66(2):239–246.
73. Astrup A, Ryan L, Grunwald GK, Storgaard M, Saris W, Melanson E et al. The role of dietary fat in
body fatness: evidence from a preliminary meta-analysis of ad libitum low-fat dietary intervention studies.
Br J Nutr 2000; 83(Suppl 1):S25–S32.
74. Thomas CD, Peters JC, Reed GW, Abumrad NN, Sun M, Hill JO. Nutrient balance and energy expenditure
during ad libitum feeding of high-fat and high-carbohydrate diets in humans. Am J Clin Nutr 1992;
55(5):934–942.
75. Hill JO, Drougas H, Peters JC. Obesity treatment: can diet composition play a role. Ann Intern Med
1993; 119(7 Pt 2):694–697.
76. Due A, Toubro S, Skov AR, Astrup A. Effect of normal-fat diets, either medium or high in protein, on
body weight in overweight subjects: a randomised 1-year trial. Int J Obes Relat Metab Disord 2004;
28(10):1283–1290.
77. Ludwig DS. Dietary glycemic index and obesity. J Nutr 2000; 130(2S Suppl):280S–283S.
78. Golay A, Allaz AF, Morel Y, de Tonnac N, Tankova S, Reaven G. Similar weight loss with low- or
high-carbohydrate diets. Am J Clin Nutr 1996; 63(2):174–178.
79. Stern L, Iqbal N, Seshadri P, Chicano KL, Daily DA, McGrory J et al. The effects of low-carbohydrate
versus conventional weight loss diets in severely obese adults: one-year follow-up of a randomized
trial. Ann Intern Med 2004; 140(10):778–785.
80. Samaha FF, Iqbal N, Seshadri P, Chicano KL, Daily DA, McGrory J et al. A low-carbohydrate as
compared with a low-fat diet in severe obesity. N Engl J Med 2003; 348(21):2074–2081.
81. Nordmann AJ, Nordmann A, Briel M, Keller U, Yancy WS, Jr, Brehm BJ et al. Effects of low-carbo-
hydrate vs low-fat diets on weight loss and cardiovascular risk factors: a meta-analysis of randomized
controlled trials. Arch Intern Med 2006; 166(3):285–293.
82. Horton TJ, Drougas H, Brachey A, Reed GW, Peters JC, Hill JO. Fat and carbohydrate overfeeding in
humans: different effects on energy storage. Am J Clin Nutr 1995; 62(1):19–29.
83. Silva JE. The thermogenic effect of thyroid hormone and its clinical implications. Ann Intern Med
2003; 139(3):205–213.
84. Rosenbaum M, Hirsch J, Murphy E, Leibel RL. Effects of changes in body weight on carbohydrate
metabolism, catecholamine excretion, and thyroid function. Am J Clin Nutr 2000; 71(6):1421–1432.
85. Snitker S, Macdonald I, Ravussin E, Astrup A. The sympathetic nervous system and obesity: role in
aetiology and treatment. Obes Rev 2000; 1(1):5–15.
86. Lowell BB, Bachman ES. Beta-adrenergic receptors, diet-induced thermogenesis, and obesity. J Biol
Chem 2003; 278(32):29385–29388.
87. Tataranni PA, Young JB, Bogardus C, Ravussin E. A low sympathoadrenal activity is associated with
body weight gain and development of central adiposity in Pima Indian men. Obes Res 1997; 5(4):
341–347.
88. Arch JR, Ainsworth AT, Cawthorne MA, Piercy V, Sennitt MV, Thody VE et al. Atypical beta-adreno-
ceptor on brown adipocytes as target for anti-obesity drugs. Nature 1984; 309(5964):163–165.
89. Himms-Hagen J, Cui J, Danforth E, Jr, Taatjes DJ, Lang SS, Waters BL et al. Effect of CL-316,243,
a thermogenic beta 3-agonist, on energy balance and brown and white adipose tissues in rats. Am J
Physiol 1994; 266(4 Pt 2):R1371–R1382.
90. Levin BE, Triscari J, Marquet E, Sullivan AC. Dietary obesity and neonatal sympathectomy. I. Effects
on body composition and brown adipose. Am J Physiol 1984; 247(6 Pt 2):R979–R987.
Chapter 4 / Central Integration of Environmental and Endogenous Signals 101
91. Rohrer DK, Chruscinski A, Schauble EH, Bernstein D, Kobilka BK. Cardiovascular and meta-
bolic alterations in mice lacking both beta1- and beta2-adrenergic receptors. J Biol Chem 1999;
274(24):16701–16708.
92. Susulic VS, Frederich RC, Lawitts J, Tozzo E, Kahn BB, Harper ME et al. Targeted disruption of the
beta 3-adrenergic receptor gene. J Biol Chem 1995; 270(49):29483–29492.
93. Bachman ES, Hampton TG, Dhillon H, Amende I, Wang J, Morgan JP et al. The metabolic and car-
diovascular effects of hyperthyroidism are largely independent of beta-adrenergic stimulation. Endo-
crinology 2004; 145(6):2767–2774.
94. Leite A, Neto JA, Leyton JF, Crivellaro O, el Dorry HA. Phosphofructokinase from bumblebee flight
muscle. Molecular and catalytic properties and role of the enzyme in regulation of the fructose 6-phos-
phate/fructose 1,6-bisphosphate cycle. J Biol Chem 1988; 263(33):17527–17533.
95. Block BA, O’Brien J, Meissner G. Characterization of the sarcoplasmic reticulum proteins in the
thermogenic muscles of fish. J Cell Biol 1994; 127(5):1275–1287.
96. Denborough M. Malignant hyperthermia. Lancet 1998; 352(9134):1131–1136.
97. Ducreux S, Zorzato F, Muller C, Sewry C, Muntoni F, Quinlivan R et al. Effect of ryanodine receptor
mutations on interleukin-6 release and intracellular calcium homeostasis in human myotubes from
malignant hyperthermia-susceptible individuals and patients affected by central core disease. J Biol
Chem 2004; 279(42):43838–43846.
98. Guan HP, Li Y, Jensen MV, Newgard CB, Steppan CM, Lazar MA. A futile metabolic cycle activated
in adipocytes by antidiabetic agents. Nat Med 2002; 8(10):1122–1128.
99. Ntambi JM, Miyazaki M, Stoehr JP, Lan H, Kendziorski CM, Yandell BS et al. Loss of stearoyl-CoA
desaturase-1 function protects mice against adiposity. Proc Natl Acad Sci USA 2002; 99(17):11482–
11486.
100. Smith SJ, Cases S, Jensen DR, Chen HC, Sande E, Tow B et al. Obesity resistance and multiple
mechanisms of triglyceride synthesis in mice lacking Dgat. Nat Genet 2000; 25(1):87–90.
101. Stone SJ, Myers HM, Watkins SM, Brown BE, Feingold KR, Elias PM et al. Lipopenia and skin bar-
rier abnormalities in DGAT2-deficient mice. J Biol Chem 2004; 279(12):11767–11776.
102. Abu-Elheiga L, Matzuk MM, Abo-Hashema KA, Wakil SJ. Continuous fatty acid oxidation and
reduced fat storage in mice lacking acetyl-CoA carboxylase 2. Science 2001; 291(5513):2613–2616.
103. Ludwig EH, Mahley RW, Palaoglu E, Ozbayrakci S, Balestra ME, Borecki IB et al. DGAT1 promoter
polymorphism associated with alterations in body mass index, high density lipoprotein levels and
blood pressure in Turkish women. Clin Genet 2002; 62(1):68–73.
104. Minokoshi Y, Kim YB, Peroni OD, Fryer LG, Muller C, Carling D et al. Leptin stimulates fatty-acid
oxidation by activating AMP-activated protein kinase. Nature 2002; 415(6869):339–343.
105. Minokoshi Y, Alquier T, Furukawa N, Kim YB, Lee A, Xue B et al. AMP-kinase regulates food intake
by responding to hormonal and nutrient signals in the hypothalamus. Nature 2004; 428(6982):569–
574.
106. Lowell BB, Susulic V, Hamann A, Lawitts JA, Himms-Hagen J, Boyer BB et al. Development of obe-
sity in transgenic mice after genetic ablation of brown adipose tissue. Nature 1993; 366(6457):740–
742.
107. Robidoux J, Martin TL, Collins S. Beta-adrenergic receptors and regulation of energy expenditure: a
family affair. Annu Rev Pharmacol Toxicol 2004; 44:297–323.
108. Weyer C, Gautier JF, Danforth E, Jr. Development of beta 3-adrenoceptor agonists for the treatment of
obesity and diabetes – an update. Diabetes Metab 1999; 251):11–21.
109. Nicholls DG. A history of UCP1. Biochem Soc Trans 2001; 29Pt 6):751–755.
110. Zhang CY, Baffy G, Perret P, Krauss S, Peroni O, Grujic D et al. Uncoupling protein-2 negatively
regulates insulin secretion and is a major link between obesity, beta cell dysfunction, and type 2 dia-
betes. Cell 2001; 1056):745–755.
111. Arsenijevic D, Onuma H, Pecqueur C, Raimbault S, Manning BS, Miroux B et al. Disruption of the
uncoupling protein-2 gene in mice reveals a role in immunity and reactive oxygen species production.
Nat Genet 2000; 26(4):435–439.
112. Clapham JC, Arch JR, Chapman H, Haynes A, Lister C, Moore GB et al. Mice overexpressing human
uncoupling protein-3 in skeletal muscle are hyperphagic and lean. Nature 2000; 406(6794):415–418.
102 Kelesidis, Kelesidis, Mantzoros
113. Havel PJ. Update on adipocyte hormones: regulation of energy balance and carbohydrate/lipid metab-
olism. Diabetes 2004; 53(Suppl 1):S143–S151.
114. Klaus S. Adipose tissue as a regulator of energy balance. Curr Drug Targets 2004; 5(3):241–250.
115. Goran MI, Kaskoun M, Johnson R. Determinants of resting energy expenditure in young children.
J Pediatr 1994; 125(3):362–367.
116. Campfield LA, Smith FJ, Burn P. Strategies and potential molecular targets for obesity treatment. Sci-
ence 1998; 280(5368):1383–1387.
117. Harper JA, Dickinson K, Brand MD. Mitochondrial uncoupling as a target for drug development for
the treatment of obesity. Obes Rev 2001; 2(4):255–265.
118. Gura T. Obesity drug pipeline not so fat. Science 2003; 299(5608):849–852.
119. O’Rahilly S. Leptin: defining its role in humans by the clinical study of genetic disorders. Nutr Rev
2002; 60(10 Pt 2):S30–S34.
120. Farooqi IS, Keogh JM, Kamath S, Jones S, Gibson WT, Trussell R et al. Partial leptin deficiency and
human adiposity. Nature 2001; 414(6859):34–35.
121. Heymsfield SB, Greenberg AS, Fujioka K, Dixon RM, Kushner R, Hunt T et al. Recombinant leptin
for weight loss in obese and lean adults: a randomized, controlled, dose-escalation trial. JAMA 1999;
282(16):1568–1575.
122. Grover GJ, Mellstrom K, Ye L, Malm J, Li YL, Bladh LG et al. Selective thyroid hormone receptor-
beta activation: a strategy for reduction of weight, cholesterol, and lipoprotein (a) with reduced car-
diovascular liability. Proc Natl Acad Sci USA 2003; 100(17):10067–10072.
123. Wagner RL, Huber BR, Shiau AK, Kelly A, Cunha Lima ST, Scanlan TS et al. Hormone selectivity in
thyroid hormone receptors. Mol Endocrinol 2001; 15(3):398–410.
124. Daly PA, Krieger DR, Dulloo AG, Young JB, Landsberg L. Ephedrine, caffeine and aspirin: safety and
efficacy for treatment of human obesity. Int J Obes Relat Metab Disord 1993; 17(Suppl 1):S73–S78.
125. Yanovski SZ, Yanovski JA. Obesity. N Engl J Med 2002; 346(8):591–602.
126. Connoley IP, Liu YL, Frost I, Reckless IP, Heal DJ, Stock MJ. Thermogenic effects of sibutramine and
its metabolites. Br J Pharmacol 1999; 126(6):1487–1495.
127. Thearle M, Aronne LJ. Obesity and pharmacologic therapy. Endocrinol Metab Clin North Am 2003;
32(4):1005–1024.
128. Jessen AB, Toubro S, Astrup A. Effect of chewing gum containing nicotine and caffeine on energy
expenditure and substrate utilization in men. Am J Clin Nutr 2003; 77(6):1442–1447.
129. Hofstetter A, Schutz Y, Jequier E, Wahren J. Increased 24-hour energy expenditure in cigarette smok-
ers. N Engl J Med 1986; 314(2):79–82.
130. Astrup A, Toubro S, Christensen NJ, Quaade F. Pharmacology of thermogenic drugs. Am J Clin Nutr
1992; 55(1 Suppl):246S–248S.
131. Arch JR. Beta(3)-adrenoceptor agonists: potential, pitfalls and progress. Eur J Pharmacol 2002;
440(2/3):99–107.
132. Hu B, Jennings LL. Orally bioavailable beta 3-adrenergic receptor agonists as potential therapeutic
agents for obesity and type-II diabetes. Prog Med Chem 2003; 41:167–194.
133. Wing RR. Physical activity in the treatment of the adulthood overweight and obesity: current evidence
and research issues. Med Sci Sports Exerc 1999; 31(11 Suppl):S547–S552.
134. Ross R, Dagnone D, Jones PJ, Smith H, Paddags A, Hudson R et al. Reduction in obesity and related
comorbid conditions after diet-induced weight loss or exercise-induced weight loss in men. A ran-
domized, controlled trial. Ann Intern Med 2000; 133(2):92–103.
135. McGuire MT, Wing RR, Hill JO. The prevalence of weight loss maintenance among American adults.
Int J Obes Relat Metab Disord 1999; 23(12):1314–1319.
136. Boutelle KN, Kirschenbaum DS. Further support for consistent self-monitoring as a vital component
of successful weight control. Obes Res 1998; 6(3):219–224.
137. Rampersaud GC, Pereira MA, Girard BL, Adams J, Metzl JD. Breakfast habits, nutritional sta-
tus, body weight, and academic performance in children and adolescents. J Am Diet Assoc 2005;
105(5):743–760.
138. Allen YS, Adrian TE, Allen JM, Tatemoto K, Crow TJ, Bloom SR et al. Neuropeptide Y distribution
in the rat brain. Science 1983; 221(4613):877–879.
Chapter 4 / Central Integration of Environmental and Endogenous Signals 103
139. Hillebrand JJ , de Wied D , Adan RA . Neuropeptides, food intake and body weight regulation:
a hypothalamic focus. Peptides 2002; 23(12):2283–2306.
140. Sawchenko PE, Pfeiffer SW. Ultrastructural localization of neuropeptide Y and galanin immuno-
reactivity in the paraventricular nucleus of the hypothalamus in the rat. Brain Res 1988; 474(2):231–245.
141. Hu Y, Bloomquist BT, Cornfield LJ, DeCarr LB, Flores-Riveros JR, Friedman L et al. Identification
of a novel hypothalamic neuropeptide Y receptor associated with feeding behavior. J Biol Chem 1996;
271(42):26315–26319.
142. Shiraishi T, Oomura Y, Sasaki K, Wayner MJ. Effects of leptin and orexin-A on food intake and feeding
related hypothalamic neurons. Physiol Behav 2000; 71(3/4):251–261.
143. Akabayashi A, Watanabe Y, Wahlestedt C, McEwen BS, Paez X, Leibowitz SF. Hypothalamic neuropeptide
Y, its gene expression and receptor activity: relation to circulating corticosterone in adrenalectomized
rats. Brain Res 1994; 665(2):201–212.
144. McKibbin PE, Cotton SJ, McCarthy HD, Williams G. The effect of dexamethasone on neuropeptide
Y concentrations in specific hypothalamic regions. Life Sci 1992; 51(16):1301–1307.
145. Stanley BG, Lanthier D, Chin AS, Leibowitz SF. Suppression of neuropeptide Y-elicited eating by
adrenalectomy or hypophysectomy: reversal with corticosterone. Brain Res 1989; 501(1):32–36.
146. Tempel DL, Leibowitz SF. Adrenal steroid receptors: interactions with brain neuropeptide systems in
relation to nutrient intake and metabolism. J Neuroendocrinol 1994; 6(5):479–501.
147. Giraudo SQ, Kotz CM, Grace MK, Levine AS, Billington CJ. Rat hypothalamic NPY mRNA and
brown fat uncoupling protein mRNA after high-carbohydrate or high-fat diets. Am J Physiol 1994;
266(5 Pt 2):R1578–R1583.
148. Wang J, Akabayashi A, Dourmashkin J, Yu HJ, Alexander JT, Chae HJ et al. Neuropeptide Y in relation
to carbohydrate intake, corticosterone and dietary obesity. Brain Res 1998; 802(1/2):75–88.
149. Welch CC, Kim EM, Grace MK, Billington CJ, Levine AS. Palatability-induced hyperphagia increases
hypothalamic dynorphin peptide and mRNA levels. Brain Res 1996; 721(1/2):126–131.
150. Campfield LA, Smith FJ. Blood glucose dynamics and control of meal initiation: a pattern detection
and recognition theory. Physiol Rev 2003; 83(1):25–58.
151. Campfield LA, Smith FJ, Rosenbaum M, Hirsch J. Human eating: evidence for a physiological basis
using a modified paradigm. Neurosci Biobehav Rev 1996; 20(1):133–137.
152. Krysiak R, Obuchowicz E, Herman ZS. Interactions between the neuropeptide Y system and the
hypothalamic-pituitary-adrenal axis. Eur J Endocrinol 1999; 140(2):130–136.
153. Billington CJ, Briggs JE, Grace M, Levine AS. Effects of intracerebroventricular injection of neuropeptide
Y on energy metabolism. Am J Physiol 1991; 260(2 Pt 2):R321–R327.
154. Baskin DG, Hahn TM, Schwartz MW. Leptin sensitive neurons in the hypothalamus. Horm Metab Res
1999; 31(5):345–350.
155. Broberger C , Johansen J , Johansson C , Schalling M , Hokfelt T. The neuropeptide Y/agouti
gene-related protein (AGRP) brain circuitry in normal, anorectic, and monosodium glutamate-treated
mice. Proc Natl Acad Sci USA 1998; 95(25):15043–15048.
156. Chen P, Li C, Haskell-Luevano C, Cone RD, Smith MS. Altered expression of agouti-related protein
and its colocalization with neuropeptide Y in the arcuate nucleus of the hypothalamus during lactation.
Endocrinology 1999; 140(6):2645–2650.
157. Mizuno TM, Mobbs CV. Hypothalamic agouti-related protein messenger ribonucleic acid is inhibited
by leptin and stimulated by fasting. Endocrinology 1999; 140(2):814–817.
158. Wirth MM, Giraudo SQ. Agouti-related protein in the hypothalamic paraventricular nucleus: effect on
feeding. Peptides 2000; 21(9):1369–1375.
159. Small CJ, Kim MS, Stanley SA, Mitchell JR, Murphy K, Morgan DG et al. Effects of chronic
central nervous system administration of agouti-related protein in pair-fed animals. Diabetes 2001;
50(2):248–254.
160. Ghilardi N, Ziegler S, Wiestner A, Stoffel R, Heim MH, Skoda RC. Defective STAT signaling by the
leptin receptor in diabetic mice. Proc Natl Acad Sci USA 1996; 93(13):6231–6235.
161. Kim MS, Small CJ, Stanley SA, Morgan DG, Seal LJ, Kong WM et al. The central melanocortin system
affects the hypothalamo-pituitary thyroid axis and may mediate the effect of leptin. J Clin Invest 2000;
105(7):1005–1011.
104 Kelesidis, Kelesidis, Mantzoros
162. Tritos NA, Maratos-Flier E. Two important systems in energy homeostasis: melanocortins and melanin-
concentrating hormone. Neuropeptides 1999; 33(5):339–349.
163. Bahjaoui-Bouhaddi M, Fellmann D, Griffond B, Bugnon C. Insulin treatment stimulates the rat melanin-
concentrating hormone-producing neurons. Neuropeptides 1994; 27(4):251–258.
164. Sergeev VG, Akmaev IG. Effects of blockers of carbohydrate and lipid metabolism on expression of
mRNA of some hypothalamic neuropeptides. Bull Exp Biol Med 2000; 130(8):766–768.
165. Sergeyev V, Broberger C, Gorbatyuk O, Hokfelt T. Effect of 2-mercaptoacetate and 2-deoxy-d-glucose
administration on the expression of NPY, AGRP, POMC, MCH and hypocretin/orexin in the rat hypo-
thalamus. NeuroReport 2000; 11(1):117–121.
166. Toshinai K, Mondal MS, Nakazato M, Date Y, Murakami N, Kojima M et al. Upregulation of ghrelin
expression in the stomach upon fasting, insulin-induced hypoglycemia, and leptin administration.
Biochem Biophys Res Commun 2001; 281(5):1220–1225.
167. Cai XJ, Widdowson PS, Harrold J, Wilson S, Buckingham RE, Arch JR et al. Hypothalamic orexin
expression: modulation by blood glucose and feeding. Diabetes 1999; 48(11):2132–2137.
168. Mondal MS, Nakazato M, Date Y, Murakami N, Yanagisawa M, Matsukura S. Widespread distribution
of orexin in rat brain and its regulation upon fasting. Biochem Biophys Res Commun 1999; 256(3):
495–499.
169. Stricker-Krongrad A, Beck B. Modulation of hypothalamic hypocretin/orexin mRNA expression by
glucocorticoids. Biochem Biophys Res Commun 2002; 296(1):129–133.
170. Lawrence CB, Snape AC, Baudoin FM, Luckman SM. Acute central ghrelin and GH secretagogues
induce feeding and activate brain appetite centers. Endocrinology 2002; 143(1):155–162.
171. Olszewski PK, Li D, Grace MK, Billington CJ, Kotz CM, Levine AS. Neural basis of orexigenic
effects of ghrelin acting within lateral hypothalamus. Peptides 2003; 24(4):597–602.
172. Griffond B, Risold PY, Jacquemard C, Colard C, Fellmann D. Insulin-induced hypoglycemia increases
preprohypocretin (orexin) mRNA in the rat lateral hypothalamic area. Neurosci Lett 1999; 262(2):
77–80.
173. Moriguchi T, Sakurai T, Nambu T, Yanagisawa M, Goto K. Neurons containing orexin in the lateral
hypothalamic area of the adult rat brain are activated by insulin-induced acute hypoglycemia. Neurosci
Lett 1999; 264(1/3):101–104.
174. Beck B, Richy S. Hypothalamic hypocretin/orexin and neuropeptide Y: divergent interaction with
energy depletion and leptin. Biochem Biophys Res Commun 1999; 258(1):119–122.
175. Taheri S, Mahmoodi M, Opacka-Juffry J, Ghatei MA, Bloom SR. Distribution and quantification of
immunoreactive orexin A in rat tissues. FEBS Lett 1999; 457(1):157–161.
176. Wortley KE, Chang GQ, Davydova Z, Leibowitz SF. Peptides that regulate food intake: orexin gene
expression is increased during states of hypertriglyceridemia. Am J Physiol Regul Integr Comp Physiol
2003; 284(6):R1454–R1465.
177. Yamamoto Y, Ueta Y, Date Y, Nakazato M, Hara Y, Serino R et al. Down regulation of the prepro-
orexin gene expression in genetically obese mice. Brain Res Mol Brain Res 1999; 65(1):14–22.
178. Briski KP, Sylvester PW. Hypothalamic orexin-A-immunpositive neurons express Fos in response to
central glucopenia. NeuroReport 2001; 12(3):531–534.
179. Cai XJ, Evans ML, Lister CA, Leslie RA, Arch JR, Wilson S et al. Hypoglycemia activates orexin
neurons and selectively increases hypothalamic orexin-B levels: responses inhibited by feeding and
possibly mediated by the nucleus of the solitary tract. Diabetes 2001; 50(1):105–112.
180. Yamanaka A, Beuckmann CT, Willie JT, Hara J, Tsujino N, Mieda M et al. Hypothalamic orexin
neurons regulate arousal according to energy balance in mice. Neuron 2003; 38(5):701–713.
181. Gundlach AL, Burazin TC, Larm JA. Distribution, regulation and role of hypothalamic galanin
systems: renewed interest in a pleiotropic peptide family. Clin Exp Pharmacol Physiol 2001;
28(1/2):100–105.
182. Leibowitz SF. Brain peptides and obesity: pharmacologic treatment. Obes Res 1995; 3(Suppl 4):
573S–589S.
183. Tempel DL, Leibowitz SF. Diurnal variations in the feeding responses to norepinephrine, neuropeptide
Y and galanin in the PVN. Brain Res Bull 1990; 25(6):821–825.
184. Wynick D, Bacon A. Targeted disruption of galanin: new insights from knock-out studies. Neuropeptides
2002; 36(2/3):132–144.
Chapter 4 / Central Integration of Environmental and Endogenous Signals 105
185. Akabayashi A, Koenig JI, Watanabe Y, Alexander JT, Leibowitz SF. Galanin-containing neurons in
the paraventricular nucleus: a neurochemical marker for fat ingestion and body weight gain. Proc Natl
Acad Sci USA 1994; 91(22):10375–10379.
186. Leibowitz SF, Akabayashi A, Wang J. Obesity on a high-fat diet: role of hypothalamic galanin in
neurons of the anterior paraventricular nucleus projecting to the median eminence. J Neurosci 1998;
18(7):2709–2719.
187. Odorizzi M, Max JP, Tankosic P, Burlet C, Burlet A. Dietary preferences of Brattleboro rats correlated
with an overexpression of galanin in the hypothalamus. Eur J Neurosci 1999; 11(9):3005–3014.
188. Wang J, Akabayashi A, Yu HJ, Dourmashkin J, Alexander JT, Silva I et al. Hypothalamic galanin:
control by signals of fat metabolism. Brain Res 1998; 804(1):7–20.
189. Kyrkouli SE, Stanley BG, Leibowitz SF. Galanin: stimulation of feeding induced by medial hypotha-
lamic injection of this novel peptide. Eur J Pharmacol 1986; 122(1):159–160.
190. Nemeth PM, Rosser BW, Choksi RM, Norris BJ, Baker KM. Metabolic response to a high-fat diet in
neonatal and adult rat muscle. Am J Physiol 1992; 262(2 Pt 1):C282–C286.
191. MacNeil DJ, Howard AD, Guan X, Fong TM, Nargund RP, Bednarek MA et al. The role of melano-
cortins in body weight regulation: opportunities for the treatment of obesity. Eur J Pharmacol 2002;
450(1):93–109.
192. Gantz I, Fong TM. The melanocortin system. Am J Physiol Endocrinol Metab 2003; 284(3):
E468–E474.
193. Kieffer TJ, Habener JF. The adipoinsular axis: effects of leptin on pancreatic beta-cells. Am J Physiol
Endocrinol Metab 2000; 278(1):E1–E14.
194. Clegg DJ, Benoit SC, Air EL, Jackman A, Tso P, D’Alessio D et al. Increased dietary fat attenuates
the anorexic effects of intracerebroventricular injections of MTII. Endocrinology 2003; 144(7)
:2941–2946.
195. Harrold JA, Williams G, Widdowson PS. Changes in hypothalamic agouti-related protein (AGRP),
but not alpha-MSH or pro-opiomelanocortin concentrations in dietary-obese and food-restricted rats.
Biochem Biophys Res Commun 1999; 258(3):574–577.
196. Torri C, Pedrazzi P, Leo G, Muller EE, Cocchi D, Agnati LF et al. Diet-induced changes in hypothalamic
pro-opio-melanocortin mRNA in the rat hypothalamus. Peptides 2002; 23(6):1063–1068.
197. Pierroz DD, Ziotopoulou M, Ungsunan L, Moschos S, Flier JS, Mantzoros CS. Effects of acute and
chronic administration of the melanocortin agonist MTII in mice with diet-induced obesity. Diabetes
2002; 51(5):1337–1345.
198. Chen AS, Marsh DJ, Trumbauer ME, Frazier EG, Guan XM, Yu H et al. Inactivation of the mouse
melanocortin-3 receptor results in increased fat mass and reduced lean body mass. Nat Genet 2000;
26(1):97–102.
199. Yeo GS, Farooqi IS, Aminian S, Halsall DJ, Stanhope RG, O’Rahilly S. A frameshift mutation in
MC4R associated with dominantly inherited human obesity. Nat Genet 1998; 20(2):111–112.
200. Vaisse C, Clement K, Guy-Grand B, Froguel P. A frameshift mutation in human MC4R is associated
with a dominant form of obesity. Nat Genet 1998; 20(2):113–114.
201. Farooqi IS, Keogh JM, Yeo GS, Lank EJ, Cheetham T, O’Rahilly S. Clinical spectrum of obesity and
mutations in the melanocortin 4 receptor gene. N Engl J Med 2003; 348(12):1085–1095.
202. Bluher S, Ziotopoulou M, Bullen JW, Jr, Moschos SJ, Ungsunan L, Kokkotou E et al. Responsiveness
to peripherally administered melanocortins in lean and obese mice. Diabetes 2004; 53(1):82–90.
203. Hurd YL, Fagergren P. Human cocaine- and amphetamine-regulated transcript (CART) mRNA
is highly expressed in limbic- and sensory-related brain regions. J Comp Neurol 2000; 425(4):
583–598.
204. Kristensen P, Judge ME, Thim L, Ribel U, Christjansen KN, Wulff BS et al. Hypothalamic CART is
a new anorectic peptide regulated by leptin. Nature 1998; 393(6680):72–76.
205. Elias CF, Lee C, Kelly J, Aschkenasi C, Ahima RS, Couceyro PR et al. Leptin activates hypothalamic
CART neurons projecting to the spinal cord. Neuron 1998; 21(6):1375–1385.
206. Savontaus E, Conwell IM, Wardlaw SL. Effects of adrenalectomy on AGRP, POMC, NPY and CART
gene expression in the basal hypothalamus of fed and fasted rats. Brain Res 2002; 958(1):130–138.
207. Vrang N, Larsen PJ, Tang-Christensen M, Larsen LK, Kristensen P. Hypothalamic cocaine-amphetamine
regulated transcript (CART) is regulated by glucocorticoids. Brain Res 2003; 965(1/2):45–50.
106 Kelesidis, Kelesidis, Mantzoros
208. Larm JA, Gundlach AL. Galanin-like peptide (GALP) mRNA expression is restricted to arcuate
nucleus of hypothalamus in adult male rat brain. Neuroendocrinology 2000; 72(2):67–71.
209. Jureus A, Cunningham MJ, McClain ME, Clifton DK, Steiner RA. Galanin-like peptide (GALP) is a
target for regulation by leptin in the hypothalamus of the rat. Endocrinology 2000; 141(7):2703–2706.
210. Kastin AJ, Akerstrom V, Hackler L. Food deprivation decreases blood galanin-like peptide and its
rapid entry into the brain. Neuroendocrinology 2001; 74(6):423–432.
211. Krasnow SM, Fraley GS, Schuh SM, Baumgartner JW, Clifton DK, Steiner RA. A role for galanin-like
peptide in the integration of feeding, body weight regulation, and reproduction in the mouse. Endocri-
nology 2003; 144(3):813–822.
212. Lawrence CB, Baudoin FM, Luckman SM. Centrally administered galanin-like peptide modifies food
intake in the rat: a comparison with galanin. J Neuroendocrinol 2002; 14(11):853–860.
213. Richard D, Lin Q, Timofeeva E. The corticotropin-releasing factor family of peptides and CRF receptors:
their roles in the regulation of energy balance. Eur J Pharmacol 2002; 440(2/3):189–197.
214. Cai A, Wise PM. Age-related changes in the diurnal rhythm of CRH gene expression in the paraven-
tricular nuclei. Am J Physiol 1996; 270(2 Pt 1):E238–E243.
215. Moldow RL, Fischman AJ. Circadian rhythm of corticotropin releasing factor-like immunoreactivity
in rat hypothalamus. Peptides 1984; 5(6):1213–1215.
216. Arase K, York DA, Shimizu H, Shargill N, Bray GA. Effects of corticotropin-releasing factor on food
intake and brown adipose tissue thermogenesis in rats. Am J Physiol 1988; 255(3 Pt 1):E255–E259.
217. Egawa M, Yoshimatsu H, Bray GA. Effect of corticotropin releasing hormone and neuropeptide Y on
electrophysiological activity of sympathetic nerves to interscapular brown adipose tissue. Neuroscience
1990; 34(3):771–775.
218. Glowa JR, Barrett JE, Russell J, Gold PW. Effects of corticotropin releasing hormone on appetitive
behaviors. Peptides 1992; 13(3):609–621.
219. Inui A. Transgenic approach to the study of body weight regulation. Pharmacol Rev 2000; 52(1):
35–61.
220. Richard D, Huang Q, Timofeeva E. The corticotropin-releasing hormone system in the regulation of
energy balance in obesity. Int J Obes Relat Metab Disord 2000; 24 Suppl 2:S36–S39.
221. Rothwell NJ. Central effects of CRF on metabolism and energy balance. Neurosci Biobehav Rev
1990; 14(3):263–271.
222. Whitnall MH. Regulation of the hypothalamic corticotropin-releasing hormone neurosecretory system.
Prog Neurobiol 1993; 40(5):573–629.
223. Schwartz MW, Woods SC, Porte D, Jr, Seeley RJ, Baskin DG. Central nervous system control of food
intake. Nature 2000; 404(6778):661–671.
224. Heisler LK, Cowley MA, Kishi T, Tecott LH, Fan W, Low MJ et al. Central serotonin and melanocortin
pathways regulating energy homeostasis. Ann NY Acad Sci 2003; 994:169–174.
225. Wang GJ, Volkow ND, Fowler JS. The role of dopamine in motivation for food in humans: implications
for obesity. Expert Opin Ther Targets 2002; 6(5):601–609.
5 Insulin Resistance in States
of Energy Excess: Underlying
Pathophysiological Concepts
Susann Blüher and Christos S. Mantzoros
KEY POINTS
• The epidemic of obesity and associated metabolic and cardiovascular disorders are of increas-
ing prevalence and, thus, importance.
• Despite significant progress made during this past decade, the pathophysiological mecha-
nisms underlying the development of these diseases are still poorly understood.
• A dysfunctional adipose tissue is currently considered the “conditio sine qua non” for the devel-
opment of the metabolic syndrome; this may result from either an a priori limited or an exhausted
storage capacity of adipocytes in states of lipoatrophy or chronic energy excess, respectively.
• The latter is associated with hypertrophy of adipocytes and when coupled with excessive fat
deposition in muscle and liver leads to a derangement in the release of fatty acids, hormones,
adipokines, proinflammatory cytokines, and other molecules, which, in turn, result in insulin
resistance and a low grade inflammation.
• According to our current understanding, chronic inflammation may contribute further toward
the development of both insulin resistance and artherosclerosis.
• Impairment of insulin action in the periphery and activation of certain immunological
responses lead over time to the special features and comorbidites of the metabolic syndrome.
• This chapter provides information on factors and molecules involved in the pathogenesis of
insulin resistance and other aspects of the metabolic syndrome and discusses our present
understanding of the role adipokines, free fatty acids, and inflammatory markers play in the
development of this syndrome.
Key Words: Obesity, Metabolic syndrome, Insulin resistance, Pathophysiology,
Adipokines, Body fat distribution
1. INTRODUCTION
An epidemic of obesity is evolving not only in most industrial countries, but also in
many developing countries around the world. Obesity substantially increases the risk
for metabolic, cardiovascular, and orthopedic comorbidites. The degree of body fat
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_5,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
107
108 Blüher and Mantzoros
mass accumulation depends on several factors including ethnic background and genetic
makeup, gender, and age, but also neuroendocrine, environmental and societal param-
eters. Gonadal steroids may play a major role in the distribution of body fat. At the onset
of puberty, men become more muscular and have less fat, whereas women start to have a
higher percentage of body fat in relation to their muscle mass. These differences persist
throughout life and are reflected in the typical male and female fat distribution pattern.
With advancing age, both gonadal steroid and growth hormone secretion decline, result-
ing in increased accumulation of visceral fat, particularly in men. In women, higher serum
testosterone concentrations are usually associated with increased visceral fat. Thus, the
decline in growth hormone and the loss of estrogen at the time of menopause may explain
the relatively rapid increase in visceral fat in postmenopausal women. Differences in
adipose tissue cellularity have also been suggested as a possible link between obesity and
diabetes. Obese people with large subcutaneous abdominal adipocyte size are on average
more hyperinsulinemic and glucose intolerant than those with a similar degree of adipos-
ity but with relatively smaller subcutaneous abdominal adipocyte size (1).
According to the department of Health and Human Services, 30% of the US population
was obese in 2001 with prevalence rates in other developed nations either being similar
or following very closely. The prevalence of overweight or obesity in western popula-
tions is currently approximately 60% but among type 2 diabetic patients it is as high as
80% (2,3). It is anticipated that, if the same trend continues, more than 80% of American
adults will be either overweight or obese by 2020.
In general terms, obesity is the result of excessive energy stored in fat. An increased
fat mass is associated with an increase in fat cell size (hypertrophy) and/or fat cell amount
(hyperplasia). Obesity leads to the development of a cluster of metabolic and other
disturbances, collectively called the metabolic/insulin resistance syndrome, which include
(or predispose to) lipid abnormalities, arterial hypertension, impaired glucose tolerance or
diabetes, a proinflammatory state, and coagulation abnormalities, all of which lead in turn
to metabolic and cardiovascular diseases as well as certain malignancies (4–6).
Several explanations for the development of the metabolic syndrome have been pro-
posed, including ectopic fat accumulation, which apparently accompanies the obese
state, as well as dysregulation and dysfunction of adipose tissue, which, in turn, secretes
abnormal amounts of cytokines and hormones collectively called adipokines (7–9). A
major determinant in the development of the metabolic syndrome seems to be not only
the total amount of energy stored as fat but also the body fat distribution, since visceral
obesity is much more closely associated with the metabolic/insulin resistance syndrome
than overall obesity (5,6).
This chapter focuses on pathways linking obesity to the features of the metabolic
syndrome and discusses underlying pathophysiological mechanisms.
2. THE METABOLIC SYNDROME
2.1. Insulin Resistance
Insulin resistance, a state in which normal circulating levels of insulin fail to produce its
expected physiological effects, usually refers to the reduced ability of insulin to regulate
carbohydrate homeostasis by regulating glucose uptake and/or glucose production. The
resistance in carbohydrate metabolism results in increased insulin production, which
Chapter 5 / Insulin Resistance in States of Energy Excess 109
in turn may produce excessive effects of insulin in other pathways (5,10). Thus, the
consequences of insulin resistance are different in different tissues affected: in muscle,
insulin resistance leads to impaired inward transmembrane glucose transport (11), whereas
in the liver, insulin resistance is mainly associated with increased neoglucogenesis and
suppressed glycogenolysis as well as impaired liver glucose uptake (12). In adipose
tissue (both visceral and subcutaneous), insulin resistance is manifested as a reduced
insulin-mediated glucose uptake (13). Insulin resistance in metabolically active tissues
leads to compensatory hyperinsulinemia. Other tissues affected by peripheral insulin
resistance include the ovaries, where insulin resistance may result in the polycystic
ovary syndrome, and vascular cells in which the development of artherosclerosis
is the major complication. In addition, it is well established that insulin resistance may
promote carcinogenesis in several tissues (14).
2.2. Overweight and Obesity vs Weight Reduction
Up to 60% of the population and up to 80% of type 2 diabetics are currently either
overweight or obese (3). Follow up for several years of either middle-aged women in
the Nurses Health Study or men in the Health Professionals Follow-up Study has clearly
shown that the risk of developing type 2 diabetes is rising in parallel with an increasing
degree of overweight and obesity. In accordance, weight reduction is associated with
decreased incidence of type 2 diabetes (4). In the Nurses Health Study, a weight loss
of 5 kg or more reduced the risk of developing type 2 diabetes by approximately 50%
(4). This observation was later also documented in interventional studies including the
Diabetes Prevention Program (DPP), where an approximate 7% of weight reduction,
maintained for an average duration of 2.8 years, was associated with a 58% reduction
in the risk of developing type 2 diabetes in the prediabetic individuals with impaired
glucose tolerance (IGT) (15).
2.3. Body Fat Distribution/Fat Storage and Secretory Capacity
of Different Fat Depots
The distribution of adipose tissue is a major determinant of the metabolic risk
profile. In addition, it has been proposed that the fact that functional capacity of the
adipose tissue varies among subjects might offer an explanation for the incomplete
overlap between the metabolic syndrome and obesity.
Although the subcutaneous adipose tissue is the site of main energy storage, when
the storage capacity in subcutaneous fat is exhausted, the visceral fat takes over and
lipids are also deposited in several other organs including muscle and liver. Individual
and gender differences define the storage capacity of subcutaneous fat depots and thus
the moment in which energy starts to be stored in visceral fat. In general, men have a
lower subcutaneous fat storage capacity and start to accumulate fat in the visceral depot
earlier than women (5,6). In concordance with these differences of functional capacity of
adipose tissue, individuals with upper body fat accumulation or higher visceral fat mass
are more insulin resistant than those with a predominantly lower body fat accumulation
and more subcutaneous fat. This has been attributable not only to the increased sensitivity
of visceral fat to lipolytic stimuli, but also to altered secretion of adipokines by visceral
fat (16–19). Visceral fat is more active in terms of accepting and releasing free fatty
acids (FFAs) and is characterized by a different pattern of adipocytokine secretion (20).
110 Blüher and Mantzoros
Thus, central or visceral obesity is associated more closely than overall obesity with
higher risk to develop insulin resistance and related metabolic disorders and leads to an
altered plasma lipid composition (5–7).
Subcutaneous fat is the main energy storage site in addition to producing certain
levels of adipokines. Visceral fat cells produce excessive amounts of proinflammatory
adipokines including tumor necrosis factor α (TNFα), interleukin 6 (IL-6), plasminogen
activator inhibitor 1 (PAI-1), and/or decreased amounts of insulin sensitizing, antiinflam-
matory adipokines such as adiponectin (21–23). These differences in the gene expression
profile between visceral and subcutaneous fat may account for the diverging metabolic
risk between the two fat depots. Out of the 1,660 genes expressed in adipose tissue, 297
(17.9%) genes have shown a twofold or higher difference in their expression between
the visceral and subcutaneous fat depots. Many of these genes are involved in glucose
homeostasis and insulin action, such as the peroxisome proliferator activator receptor γ
(PPAR γ), or in lipid metabolism, such as the HMG CoA synthase and hormone-sensitive
lipase (23).
2.4. Dietary Patterns and Physical Activity
Healthy dietary patterns, including the low glycemic index diets and Mediterannean
type diets have received much recognition over the past few years for their association
with substantial health benefits. A cross-sectional study evaluating plasma markers and
dietary data from 987 diabetic women from the Nurses’ Health Study (NHS) revealed that
women following a Mediterranean-type dietary pattern albeit older tended to have lower
body mass indexes and waist circumferences, and had higher total energy intakes, physical
activities, and plasma adiponectin concentrations. Of the several components of the
Mediterranean dietary pattern score, alcohol, nuts, and whole grains showed the strongest
association with adiponectin concentrations (24). The significance of high circulating
adiponectin levels in the context of features of the metabolic syndrome is discussed later
on, but women in the NHS adhering closely to a Mediterranean dietary pattern had, in
addition to higher adiponectin levels, lower levels of proinflammatory adipokines, lower
degrees of insulin resistance, and lower risk for diabetes and cardiovascular disease. In
contrast, high glycemic index diet and higher consumption of sugar-sweetened beverages,
observed mainly in relation to a Western dietary pattern, are clearly associated with a
greater magnitude of weight gain and an increased risk for developing type 2 diabetes
(25–27). Recent studies suggest that long-term coffee consumption is associated with a
reduction in long-term weight gain and a statistically significantly lower risk for type 2
diabetes (28–30). A higher nut consumption has also been described to offer potential
benefits in lowering risk of type 2 diabetes in women (31). Finally, in addition to dietary
patterns, physical activity significantly improves insulin resistance, insulin sensitivity,
and the metabolic syndrome, in part by altering circulating adiponectin and expression of
adiponectin as well as adiponectin receptor mRNA in muscle, as discussed later on (32).
3. DYSFUNCTION AND DYSREGULATION OF ADIPOSE TISSUE
The prevalence of the metabolic/insulin resistance syndrome continues to increase
with the exploding prevalence of overweight and obesity. This is the case in several racial
and ethnic groups including Americans among whom the prevalence of the metabolic
Chapter 5 / Insulin Resistance in States of Energy Excess 111
syndrome is estimated to be as high as 40% (2–6). Several studies have demonstrated
that weight reduction through increased physical activity, pharmacotherapy, or bariatric
surgery is associated with a highly significant reduced risk to develop any component
of the metabolic syndrome, including impaired glucose tolerance and type 2 diabetes
(15,33–35).
Emerging data strongly support the view that adipose tissue dysregulation and
dysfunction might play a role of major significance in the pathogenesis of the insulin
resistance syndrome. A dysfunctional adipose tissue associated with hypertrophy of
adipocytes and coupled with excessive fat deposition in muscle and liver is currently
considered a “conditio sine qua non” for the development of the metabolic syndrome
(5,6). These alterations lead to a derangement in the release of fatty acids, hormones,
adipokines, cytokines, and other molecules as discussed in more detail below.
4. INSULIN RESISTANCE AS A CHRONIC INFLAMMATORY PROCESS
Mechanisms inducing a low-grade systemic inflammation have been recently suggested
to be one of the putative links between obesity, adipose tissue dysfunction, and the devel-
opment of insulin resistance (7,36). Although the exact signals and the mechanisms that
trigger the inflammatory response remain incompletely understood, chronic inflammation
is apparently not only associated with, but is also most probably causally related to the
development of insulin resistance. It has been shown that accumulation of macrophages in
adipocytes leads to an activation of inflammatory pathways (10,37,38). Markers of chronic
inflammation such as C-reactive protein (CRP), fibrinogen, TNFα and IL-6, and/or circu-
lating triglyceride levels are elevated in serum of obese subjects and can predict the future
development of impaired glucose tolerance and type 2 diabetes (39,40).
Although the question of how the hypertrophic adipocytes are linked to the recruit-
ment of macrophages into the adipose tissue and the establishment of a proinflamma-
tory state remains to be fully elucidated, and the consequences of these changes are far
better understood. The two most important harmful cytokines involved in this process
are currently thought to be TNFα and IL-6, whereas adiponectin appears to be the most
protective adipocytokine. Both harmful adipokines impair insulin signaling (at the level
of the insulin receptor or at postreceptor levels including the Insulin Receptor Substrates
level) as well as actions of insulin (7,41). The fact that the number of macrophages in
human adipose tissue correlates positively with the degree of obesity strengthens the
hypothesis that macrophage infiltration into adipose tissue may contribute to the de-
velopment of dysregulated adipose tissue function and initiate the process of chronic
inflammation (7).
A major focus of research has been the question whether dysfunctional and inflamed
adipose tissue can be converted into “healthy” adipose tissue again and whether the
progression of metabolic dysfunction can be stopped or reversed by modulation of the
inflammatory profile in adipose tissue. In this context, several studies have shown that
administration of thiazolidinediones (TZD), which act by binding to and activating
peroxisome proliferator-activated receptors (PPARγ), is capable of reversing inflamma-
tory properties and lipid abnormalities besides the direct and indirect effects of TZDs
to improve insulin resistance, including increase of circulating levels of adiponectin, an
endogenous insulin sensitizer (42). Importantly, TZDs improve glycemic control and
enhance insulin sensitivity despite the paradoxical weight gain seen with TZD treatment.
112 Blüher and Mantzoros
The latter seems to be attributable to the fact that TZDs may redistribute fat within the
body by reducing visceral and hepatic fat mass and increasing subcutaneous fat depots.
Since TZDs may also lead to fluid retention, osteoporosis, and other complications, it
has been proposed that development of non-thiazolidinedione, selective PPARγ modula-
tors (SPARMs) could hopefully lead to availability of effective medications that could
result in increasing adiponectin levels and insulin sensitization without any side effects
(43). INT-131, a compound in development by Intekrin is the one in the most advanced
stages of development in this area.
5. IMPACT OF FREE FATTY ACIDS AND LIPID METABOLISM
ON INSULIN RESISTANCE: EFFECTS OF LIPOTOXICITY
Insulin inhibits lipolysis in adipose tissue and promotes the transfer of FFAs from
circulating lipoproteins to the adipose tissue. Thus, in states of insulin resistance, FFA
levels increase in the circulation due to unrestrained lipolysis and decreased clearance of
FFAs in the periphery; this phenomenon leads also to an increase of triglycerides (TG)
(10). Circulating levels of FFAs are increased in obese subjects and have been proposed
to be a major contributor to peripheral insulin resistance (44,45) initiating thus a vicious
cycle. Chronically elevated serum FFA levels stimulate gluconeogenesis, induce insulin
resistance at the level of liver and muscle, and impair insulin secretion in genetically
predisposed individuals (43). Increased FFA levels also tend to increase triglyceride
accumulation in both liver and skeletal muscle, and this correlates with the degree of
insulin resistance in these tissues (46,47). Serum triglycerides, which are in a state of
constant turnover, and their metabolites such as acyl coenzymes A, ceramides, and dia-
cylglycerol also contribute toward both impaired hepatic and peripheral insulin action.
In addition, nonesterified fatty acids are raised in obese subjects (both, diabetic and
nondiabetic) following enhanced adipocyte lipolysis. Increased fatty acid concentrations
lead to enhanced insulin secretion in the short term and significant (even total) inhibition
of insulin secretion as early as 24 h thereafter (48,49). This sequence of events is fre-
quently called lipotoxicity (50). Accumulating evidence suggests that such lipotoxicity
may also be an important contributor to the pancreatic β cell dysfunction seen in type
2 diabetic patients (48,51). Since the magnitude of the effects of lipotoxicity has been
questioned by some investigators, this area remains an active area of research.
As previously described, when the classical fat depots are filled to capacity, other
storage depots may be used for the storage of excess fat, namely liver and muscle. The
failure of adipose tissue to take up more fat absorbed by the digestive tract leads to an
excessive postprandial lipid flux toward muscle and liver and to a decreased clearance
of triglyceride rich lipoprotein particles. The interplay of these particles with HDL and
LDL cholesterol leads to the typical dyslipidemic profile, whereas the increased avail-
ability of (FFAs) has direct effects on the liver (9,52).
6. LIPODYSTROPHY AND INSULIN RESISTANCE
Similar to states of energy excess leading to obesity, congenital forms of lipodystrophy in
humans, i.e., states characterized by selective loss of subcutaneous and visceral fat, are also
associated with metabolic abnormalities (hyperglycemia, insulin resistance, dyslipidemia)
in humans (53). Insufficient adipose tissue storage capacity may in turn lead to excessive
Chapter 5 / Insulin Resistance in States of Energy Excess 113
energy storage in fat, skeletal muscle, and liver. This is in turn linked to the development
of severe insulin resistance in these organs. Patients with generalized lipodystrophy repre-
sent thus another model of human ectopic fat deposition. In accordance with the concept of
ectopic fat accumulation as a contributing factor for obesity-associated insulin resistance
and related metabolic disorders, these subjects also have abnormal secretion of proinflam-
matory cytokines and abnormally low circulating levels of two adipokines, i.e., leptin and
adiponectin (53). The impact of an abnormal secretion pattern of those adipokines on lipid
metabolism and the pathogenesis of the metabolic syndrome is discussed later on.
Recent studies support the concept that insulin resistance in one of the contributing
factors to the development of dyslipidemia seen in the metabolic syndrome (10), but it
has also been proposed that elevated FFAs and triglyceride levels also contribute to exag-
geration of insulin resistance through a lipotoxicity mechanism. Moreover, the classic
diabetic dyslipidemia could be considered as the main clinical manifestation of adipose
tissue failure, i.e., lack of adipose tissue storage capacity either directly (lipoatrophy) or
indirectly i.e., because existing adipose tissue stores are filled to capacity (9,54).
7. THE ROLE OF ADIPOKINES IN INSULIN RESISTANCE
The discovery of the adipocyte secreted hormone leptin in December 1994 has resulted
in a dramatically altered view of the role the adipose tissue plays in human physiology. In
addition to its classical physiological functions (heat insulation, mechanical cushioning,
storage site for triglycerides), the adipose tissue is now recognized as an active endo-
crine organ that produces a variety of bioactive peptides (adipokines) as well as inflam-
matory and antiinflammatory molecules including leptin, adiponectin, TNFα, IL-6, IL-18,
CRP, PAI-1, and many others (7,9,55). Some of these molecules are almost exclusively
expressed in adipose tissue (e.g., leptin, adiponectin), while others are produced by both
adipose tissue and adipose tissue-resident macrophages as well as other organs or systems
(e.g., TNFα, IL-6, PAI-1). With the exception of adiponectin, which is decreased, all other
adipokines and inflammatory markers are increased in overweight and obese individuals.
7.1. Adiponectin
Adiponectin is an adipocyte secreted endogenous insulin sensitizer almost exclu-
sively expressed in adipocytes. Adiponectin expression is higher in subcutaneous than
in visceral fat, which might offer an explanation for the negative correlation between
circulating adiponectin levels and insulin resistance (56). This negative correlation is
independent of body mass index (57). Circulating adiponectin levels are reduced in
obesity, insulin resistance, and type 2 diabetes (58). In contrast to most other adipok-
ines, adiponectin exerts profound beneficial actions including insulin sensitizing, anti-
diabetogenic, anti-inflammatory/-proliferative, and anti-atherogenic effects. Up to now,
two adiponectin receptors (AdipoR1 and AdipoR2) have been described and are mainly
expressed in liver and muscle (59–66). Adiponectin increases fatty acid oxidation in
skeletal muscle, promotes glucose utilization, and reduces hepatic glucose production,
resulting thus in an increase of insulin sensitivity (9,67). Animal studies have shown that
adiponectin deficiency plays an important role in the pathogenesis of insulin resistance,
as adiponectin knockout mice develop insulin resistance that is reversed by adiponectin
administration (61). In addition, circulating adiponectin levels correlate positively with
insulin sensitivity in rodents and humans and predict the development of insulin resistance,
114 Blüher and Mantzoros
diabetes, and cardiovascular disease as well as certain malignancies associated with
obesity and the metabolic syndrome (62,63, 68–71).
In addition to its insulin-sensitizing effects, adiponectin has antiinflammatory properties
and may also protect against development or progression of atherosclerosis (72,73).
Thus, observational studies have shown that not only adiponectin, but also AdipoR1 and
AdipoR2 are all associated with body composition, insulin sensitivity, and metabolic
parameters. A healthy diet, i.e. a low glycemic index diet (74,75) and a mediterannean
type diet (76) also increase circulating adiponectin levels. Intensive, but probably not
moderate physical training increases circulating adiponectin and mRNA expression of
its receptors in muscle, and this may in turn mediate the improvement of insulin resist-
ance and the metabolic syndrome in response to exercise (32). A 7% reduction in body
weight by lifestyle modification for 6 months results in a significant increase in plasma
adiponectin levels in obese type 2 diabetic patients with insulin resistance (77). These
effects of weight loss and lifestyle modification on adiponectin levels are in agreement
with the observation that these interventions decrease the risk for diabetes and that
subjects with high adiponectin concentrations are less likely to develop type 2 diabetes
than those with lower concentrations (78).
The role of the two adiponectin receptors, AdipoR1 and AdipoR2, in the regulation of
energy homeostasis and glucose metabolism is now being extensively studied in rodents
and humans. The development of obesity by hypercaloric feeding in mice is associated
with an altered expression/secretion profile of adiponectin and its receptors in muscle and
liver (79). In addition, adiponectin and both adiponectin receptors seem to be involved in
the improvement of insulin sensitivity associated with ciliary neurotrophic factor (CNTF)-
induced weight loss (80). The mechanisms by which adiponectin improves insulin
sensitivity have not yet been fully elucidated. One proposed mechanism is the activation
of adenosine monophosphate-activated protein kinase (AMPK) in skeletal muscle and
liver, in addition to enhancing insulin-stimulated glucose uptake into fat and muscle
and suppressing hepatic glucose production as well as stimulating fatty acid oxidation.
Through the stimulation of fatty acid oxidation, circulating FFAs are further decreased
and the actions of insulin are improved (72).
7.2. Leptin
Leptin is the prototype adipokine, which is almost exclusively expressed in adipose
tissue and more so in subcutaneous fat (81). According to our current understanding,
leptin’s main function is to inform several organs of the organism that there is “enough
energy to sustain life.” This hormone exerts direct effects in metabolically active tis-
sues and/or indirect effects by activating hypothalamic centers via leptin receptors.
Circulating leptin levels are increased in obese subjects and decreased in leaner subjects
and/or in response to food deprivation (82). Its key functions include the regulation of
food intake/energy expenditure, the regulation of neuroendocrine and immune function,
and the modulation of glucose and fat metabolism by improving insulin sensitivity and
reducing intracellular lipids (55,66).
Animal studies have shown that leptin administration has an insulin sensitizing effect in
muscle cells and adipocytes (83–85). In humans, mutations of the leptin gene have been
associated with severe obesity, glucose intolerance, and insulin resistance, which are reversed
Chapter 5 / Insulin Resistance in States of Energy Excess 115
by leptin administration (86–88). The long-term effects of leptin replacement have been
intensely studied in uncontrolled studies in patients with rare syndromes of complete, mostly
congenital, lipoatrophy and severe insulin resistance or partial lipoatrophy and milder insulin
resistance/metabolic syndrome induced by administration of highly active antiretrovirals
(HAART) in HIV positive patients. Leptin administration in replacement doses significantly
improved glycemia, dyslipidemia, and hepatic steatosis in these hypoleptinemic patients
with severe insulin resistance (89,90) and improved lipidemia and insulin resistance in HIV
positive patients (91,92).
Whether elevated leptin levels contribute toward the development of the inflam-
mation associated with obesity, type 2 diabetes, and atherosclerosis needs to be fully
elucidated. Suggested pathways include direct actions on macrophages to augment their
phagocytic activity and to increase production of other inflammatory cytokines (93,94).
However, initial studies in humans do not support a role for increased leptin levels in
this respect. The exact role of leptin in influencing and regulating neuroendocrine and
immune function as well as energy homeostasis remains a subject of intense research
efforts (55,66,95).
7.3. Resistin
Resistin is an adipokine that has been proposed to correlate closely with hepatic insu-
lin resistance, and circulating resistin levels and resistin expression in adipose tissue was
proposed to be increased in type 2 diabetes and obesity (96–98). However, recent data on
a potential association between resistin and insulin resistance have been controversial.
Additional studies are needed to fully understand the molecular and cellular mechanisms
of action of this adipokine (99,100).
7.4. Visfatin
Visfatin is a recently discovered adipokine. It was first described in 2005 and seems
to be associated to the pathogenesis of obesity and impaired glucose homeostasis. In
the initial visfatin study, it was proposed that the protein is mainly produced in visceral
adipose tissue and that its expression is increased in states of insulin resistance. The
authors also reported that visfatin directly binds to the insulin receptor and that it excerts
insulin-like effects in vivo and in vitro (101). Meanwhile other groups have reported that
visfatin is also produced by a variety of other cells and that it acts as a multifunctional
protein and enzyme (9). To date, the role of visfatin in adipogenesis and glucose homeo-
stasis remains controversial. The distinct role of visfatin in the pathogenesis of insulin
resistance and its impact in states of energy excess needs to be fully elucidated by care-
fully designed studies in the future.
7.5. Retinol-Binding-Protein 4 (RBP4)
Another promising adipocytokine, the role of which also remains to be fully eluci-
dated, is retinol-binding-protein 4 (RBP4). RBP4, the only transporter protein for vita-
min A, retinol, has been proposed to be elevated in obesity and type 2 diabetes and is
decreased with inflammation or infection (102). RBP4 was discovered as a molecule
that may regulate the expression of glucose transporter 4 (GLUT4), the most important
insulin-stimulated glucose transporter, which is increased in states of insulin resistance
116 Blüher and Mantzoros
and leads to an impaired glucose uptake into adipocytes and progressing glucose intol-
erance. Several but not all groups have also reported that there is an association between
RBP4 and insulin resistance, obesity, and other features of the metabolic syndrome
(lipid profile, HOMA index, arterial hypertension, proinflammatory markers like CRP
or IL-6) (9). The exact mechanism underlying these associations needs to be studied in
more detail. Since data on the role of RBP4 in humans are controversial, more studies
of this molecule are clearly needed to fully understand its physiological role in energy
homeostasis and insulin resistance.
7.6. Tumor Necrosis Factor a (TNFα)
TNFα is a potent proinflammatory cytokine implicated in the development of insu-
lin resistance and type 2 diabetes as well as atherosclerosis (103). Circulating TNFα
levels and/or levels of the soluble TNFα receptor, a long-term marker of TNFα sys-
temic activation, are increased in both obese nondiabetic individuals (104) and in type
2 diabetes (105). TNFα is structurally similar but functionally opposite to adiponectin,
and these molecules are reciprocally regulated. Studies in genetically obese animals
suggest that increased release of TNFα from adipocytes may play a major and direct
role in the impairment of insulin action (106,107). TNFα influences insulin signaling
through impairing serine phosphorylation of insulin receptor and insulin receptor sub-
strate-1, inhibiting thus insulin action at the organ level through autocrine and paracrine
mechanisms (108). TNFα may also alter glucose transporter physiology and thus impair
insulin sensitivity and glucose metabolism.
7.7. Interleukin 6 (IL-6)
IL-6 is another important proinflammatory cytokine, which may also influence insu-
lin resistance. Similar to TNFα, IL-6 regulates hepatic production of CRP and other
acute phase proteins. In animal studies, IL-6 has been implicated in the development of
insulin resistance in muscle and may also be involved in β cell apoptosis (109). IL-6 levels
are elevated in type 2 diabetic subjects and correlate with severity of inflammation as
well as glucose intolerance (110,111). The interrelationship between the two proinflam-
matory cytokines, TNFα and IL-6, is complex, since not only TNFα stimulates IL-6
production and consequently CRP production, but IL-6 also exerts a feed back inhibitory
effect on TNFα production (112). Intervention programs that mainly increase IL-6, such
as physical activity, may have an antiinflammatory effect through suppression of TNFα,
which is one of the major inducers of inflammation (113).
7.8. Plasminogen Activator Inhibitor-1 (PAI-1)
Plasminogen activator inhibitor-1 (PAI-1) is another cytokine that may link obesity
to type 2 diabetes and cardiovascular disease. This serine protease inhibits the fibrino-
lytic cascade. Elevated PAI-1 levels cause an imbalance accelerating the atherosclerotic
process (114). Adipose tissue is one of the major sources of PAI-1, and circulating levels
are elevated in obese and diabetic subjects. It has also been noted that hyperinsulinemia,
which usually accompanies insulin resistant states, is a potent stimulus for PAI-1 production
by adipose tissue (115,116).
Chapter 5 / Insulin Resistance in States of Energy Excess 117
8. SUMMARY AND CONCLUSIONS
Obesity-related insulin resistance and the metabolic syndrome is a complex state the
pathophysiology of which remains poorly understood. The prevalence of the metabolic
syndrome has been increasing during the past few years, and this has generated a tremen-
dous research activity in this area. However, even more intense research is needed to
further elucidate the molecular and cellular mechanisms underlying this important pub-
lic health problem and to potentially provide better therapeutic options for the patients
suffering from this syndrome.
REFERENCES
1. Weyer C, Foley JE, Bogardus PA, Tataranni REP. Enlarged subcutaneous abdominal adipocyte size, but not obes-
ity itself, predicts type 2 diabetes independent of insulin resistance. Diabetologia 2000; 43: 1498–1506.
2. Tunstall-Pedoe H. Preventing Chronic Diseases. A Vital Investment: WHO Global Report. Geneva:
World Health Organization, 2005, pp 200. CHF 30.00. ISBN 92 4 1563001. Also published on http://
www.who.int/chp/chronic_disease_report/en/Int J Epidemiol 2006.
3. Mokad AH, Ford ES, Bowman BA, et al. Prevalence of obesity, diabetes and obesity-related health risk
factors 2001. JAMA 2003; 289: 76–79.
4. Field AE, Coakley EH, Must A, et al. Impact of overweight on the risk of developing common chronic
diseases during a 10-year period. Arch Int Med 2001; 161: 1581–1586.
5. Fulop T, Tessier D, Carpentier A. The metabolic syndrome. Path Biol 2006; 54: 375–386.
6. Laclaustra M, Corella D, Ordovas JM. Metabolic syndrome pathophysiology: The role of adipose tis-
sue. Nutr Metab Cardiovasc Dis 2007; 17: 125–139.
7. Murdolo G, Smith U. The dysregulated adipose tissue: A connecting link between insulin resistance,
type 2 diabetes mellitus and atherosclerosis. Nutr Metab Card Dis 2006; 16: S35–S38.
8. Yang X, Jansson PA, Nagaev I, et al. Evidence of impaired adipogenesis in insulin resistance. Biochem
Biophys Res Commun 2004; 317: 1045–1051.
9. Kiess W, Petzold S, Töpfer M, Garten A, Blüher S, Kapellen Th, Körner A, Kratzsch J. Adipocytes
and adipose tissue. Best Pract Res Clin Endocrinol Metab 2008; 22: 135–153.
10. Sweeney L, Brennan AM, Mantzoros CS. Metabolic syndrome. In Regensteiner J, Reusc J, Stewart
J and Veves A. (editors): Diabetes and Exercise. Humana Press 2009 (in press).
11. Bonadonna RC, Del Prato S, Saccomani MB et al. Transmembrane glucose transport in skeletal muscle
of patients with non-insulin dependent diabetes. J Clin Invest 1993; 92: 486–494.
12. Gastaldelli A, Baldi S, Pettiti M et al. Influence of obesity and type 2 diabetes on gluconeogenesis and
output in humans: a quantitative study. Diabetes 2000; 49: 1367–1373.
13. Virtanen KA, Iozzo P, Hallsten K. Increased fat mass compensates for insulin resistance in abdominal
obesity and type 2 diabetes: a positron-emitting tomography study. Diabetes 2005; 54: 2720–2726.
14. Barb D, Pazaitou-Panayiotou K, Mantzoros CS. Adiponectin: a link between obesity and cancer. Expert
Opin Investig Drugs 2006; 15: 917–931.
15. Knowler WC, Barrett-Conner E, Fowler E, et al. Reduction in the incidence of type 2 diabetes with
lifestyle intervention or metformin. NEJM 2002; 346: 393–403
16. Albu JB, Kovera AJ, Johnson JA. Fat distribution and health in obesity. Ann NY Acad Sci 2000;
904: 491–501.
17. Zeirath JR, Livingston JN, Thorne J, et al. Regional difference in insulin inhibition of non-esterified
fatty acid release from human adipocytes: relation to insulin receptor hosphorylation and intracellular
signaling through the insulin receptor substrate-1-pathway. Diabetologia 1998; 41: 1343–1354.
18. Arner P. Regional differences in protein production by human adipose tissue. Biochem Soc Trans 2001;
29: 72–75.
19. Motoshima H, Wu X, Sinha MK, et al. Differential regulation of adiponectin secretion from cultured
human omental and subcutaneous adipocytes: effects of insulin and rosiglitazone. J Clin Endocrinol
Metab 2002; 87: 5662–5667.
118 Blüher and Mantzoros
20. Desprès JP. Is visceral obesity the cause of the metabolic syndrome. Ann Med 2006; 38: 52–63.
21. Sewter CP, Blows F, Vidal Puig A, O’Rahilly S. Regional differences in the response of human pre-
adipocytes to PPARγ and RXRα agonists. Diabetes 2002; 51: 7218–7223.
22. Bouchard C, Depress JP, Mauriege P. Genetics and nongenetic determinants of regional fat distribution.
Endocr Rev 1993; 14: 72–93.
23. Perusse L, Rice T, Chagnon YC, et al. A genome-wide scan for abdominal fat assessed by computed
tomography in the Quebec Family Study. Diabetes 2001; 50: 614–621.
24. Mantzoros CS, Li T, Manson JE, Meigs JB, Hu FB. Circulating adiponectin levels are associated with
better glycemic control, more favorable lipid profile, and reduced inflammation in women with type 2
diabetes. J Clin Endocrinol Metab 2005; 90: 4542–4548.
25. Schulze MB, Liu S, Rimm EB, Manson JE, Willett WC, Hu FB. Glycemic index, glycemic load, and
dietary fiber intake and incidence of type 2 diabetes in younger and middle-aged women. Am J Clin
Nutr 2004; 80: 348–356.
26. Schulze MB, Manson JE, Ludwig DS, Colditz GA, Stampfer MJ, Willett WC, Hu FB. Sugar-sweetened
beverages, weight gain, and incidence of type 2 diabetes in young and middle-aged women. JAMA
2004; 292: 927–934.
27. Schulze MB, Fung TT, Manson JE, Willett WC, Hu FB. Dietary patterns and changes in body weight
in women. Obesity (Silver Spring) 2006; 14: 1444–1453.
28. Van Dam RM and Hu FB. Coffee consumption and risk of type 2 diabetes: a systematic review. JAMA
2005; 294: 97–104.
29. Lopez-Garcia E, van Dam RM, Rajpathak S, Willett WC, Manson JE, Hu FB. Changes in caffeine
intake and long-term weight change in men and women. Am J Clin Nutr 2006; 83: 674–680.
30. Williams CJ, Fargnoli JL, Hwang JJ, van Dam RM, Blackburn GL, Hu FB, Mantzoros CS. Coffee
consumption is associated with higher plasma adiponectin concentrations in women with or without
type 2 diabetes: a prospective cohort study. Diabetes Care 2008; 31: 504–507.
31. Jiang R, Manson JE, Stampfer MJ, Liu S, Willett WC, Hu FB. Nut and peanut butter consumption and
risk of type 2 diabetes in women. JAMA 2002; 288: 2554–2560.
32. Blüher M, Bullen JW, Lee JH, et al. Circulating adiponectin and expression of adiponectin receptors in
human skeletal muscle: Associations with metabolic parameters and insulin resistance and regulation
by physical training. J Clin Endocrinol Metab 2006; 91: 2310–2316.
33. Helmrich SP, Ragland DR, Leung RW et al. Physical activity and reduced occurrence of non-insulin
dependent diabetes mellitus. N Engl J Med 1991; 325: 147–152.
34. Sjostrom CD, Lissner L, Wedel H, et al. Reduction in incidence of diabetes, hypertension and lipid
disturbances after intentional weight loss induced by bariatric surgery: the SOS Intervention Study.
Obes Res 1999; 7: 477–484.
35. Dixon JB, O’Brien PE. Health outcomes of severely obese type 2 diabetic subjects 1 year after laparo-
scopic adjustable gastric banding. Diabetes Care 2002; 25(2): 358–63.
36. Hoekstra T, Geleijnse JM, Schouten EG, Kok FJ, Kluft C. Relationship of C-reactive protein with com-
ponents of the metabolic syndrome in normal-weight and overweight elderly. Nutr Metab Cardiovasc
Dis 2005; 15: 270–278.
37. Weisberg SP, McCann D, Desai M, et al. Obesity is associated with macrophage accumulation in adipose
tissue. J Clin Invest 2003; 112: 1798–1808.
38. Xu H, Barnes GT, Yang Q, et al. Chronic inflammation in fat plays a crucial role in the development
of obesity-related insulin resistance. J Clin Invest 2003; 112: 1821–1830.
39. Pickup JC, Mattock MB, Chusney GD, et al. NIDDM as a disease of the innate immune system: as-
sociations of the acute phase reactants and interleukin-6 with metabolic syndrome X. Diabetologia
1997; 40: 1286–1292.
40. Shai I, Schulze MB, Manson JE, Rexrode KM, Stampfer MJ, Mantzoros C, Hu FB. A prospective study
of soluble tumor necrosis factor-alpha receptor II (sTNF-RII) and risk of coronary heart disease among
women with type 2 diabetes. Diabetes Care 2005; 28: 1376–1382.
41. Rotter V, Nagaev I, Smith U. Interleukin-6 (IL-6) induces insulin resistance in 3T3-L1 adipocytes
and is, like IL-8 and tumor necrosis factor-α, overexpressed in human fat cells from insulin-resistant
subjects. J Biol Chem 2003; 278: 45777–45784.
42. Dandona P, Aljada A. A rational approach to pathogenesis and treatment of type 2 diabetes mellitus,
insulin resistance, inflammation, and artherosclerosis. Am J Cardiol 2002; 90: 27G–33G.
Chapter 5 / Insulin Resistance in States of Energy Excess 119
43. Bays H, Mandarino L, DeFronzo RA. Role of the adipocyte, free fatty acids, and ectopic fat in the
pathogenesis of type 2 diabetes mellitus: Peroxismal proliferatiors-activated receptor agonists provide
a rational therapeutic approach. J Clin Endocrinol Metab 2004; 89: 463–478.
44. Boden G, Chen X. Effects of fat on glucose uptake and utilization in patients with non-insulin depend-
ent diabetes. J Clin Invest 1995; 96: 1261–1268.
45. Paolisso G, Tataranni PA, Foley JE, et al. A high concentration of fasting plasma non-esterified fatty
acids is a risk factor for the development of NIDDM. Diabetologia 1995; 38: 1213–1217.
46. Greco AV, Mingrone G, Giancaterini A, et al. Insulin resistance in morbid obesity. Reversal with in-
tramyocellular fat depletion. Diabetes 2002; 51: 144–151.
47. Seppala-Lindroos A, Vehkavaara S, Hakkinen A-M, et al. Fat accumulation in the liver is associated
with defects in insulin suppression of glucose production and serum free fatty acids independent of
obesity in normal men. J Clin Endocrinol Metab 2002; 87: 3023–3028.
48. Robertson RP, Harmon J, Tran OP, Poitout V. Beta-cell glucose toxicity, lipotoxicity, and chronic
oxidative stress in type 2 diabetes. Diabetes 2004; 53: S119–S124.
49. Stumvoll M, Goldstein BJ, van Haeften TW. Type 2 diabetes: principles of pathogenesis and therapy.
Lancet 2005; 365: 1333–1346.
50. Unger RH. Lipotoxicity in the pathogenesis of obesity-dependent NIDDM: genetic and clinical impli-
cations. Diabetes 1996; 45: 273–283.
51. Shimabukuro M, Zhou YT, Leve M, Unger RH. Fatty acid induced β cell apoptosis. Proc Natl Acad
Sci USA 1998; 95: 2498–2502.
52. Avramoglu RK, Basciano H, Aedli K. Lipid andlipoprotein dysregulation in insulin resistant states.
Clin Chim Acta 2006; 368: 1–19.
53. Mantzoros CS. Syndromes of severe insulin resistance. In De Groot L (editor): Endocrinology, 5th
Edition. Philadelphia: Saunders, 2005, pp. 1133–1149.
54. Ginsberg HN. New perspective on atherogenesis: Role of abnormal triglyceride-rich lipoprotein me-
tabolism. Circulation 2002; 106: 2137–2142.
55. Fruhbeck G, Gomez-Ambrosi J, Muruzabal FJ, Burrell MA. The adipocyte: A model for integration of en-
docrine and metabolic signaling in energy metabolism regulation. Am J Physiol 2001; 280: E827–47.
56. Hotta K, Funahashi T, Bodkin NL, et al. Circulating concentrations of the adipocyte protein adiponectin
are decreased in parallel with reduced insulin sensitivity during the progression to type 2 diabetes in
rhesus monkeys. Diabetes 2001; 50: 1126–1133.
57. Yang WS, Lee WJ, Funahashi T, Tanaka S, Matsuzawa Y, Chao CL, Chen CL, Tai TY, Chaung LM.
Weight reduction increases plasma levels of an adipose-derived anti-inflammatory protein, adiponectin.
J Clin Endocrinol Metab 2001; 86: 3815–3819.
58. Brennan AM, Mantzoros CS. Leptin and adiponectin: Their role in diabetes. Curr Diab Rep 2007; 7: 1–2.
59. Yamauchi T, Kamon J, Waki H, et al. The fat derived hormone adiponectin reverses insulin resistance
associated with both lipoatrophy and obesity. Nat Med 2001; 7: 941–946.
60. Nadler ST, Stoehr JP, Schueler KL, et al. The expression of adipogenic genes is decreased in obesity
and diabetes mellitus. Proc Natl Acad Sci 2000; 97: 11371–11376.
61. Maeda N, Shimomura I, Kishida K, et al. Diet-induced insulin resistance in mice lacking adiponectin/
ACRP30. Nat Med 2002; 8: 731–737.
62. Weyer C, Funahashi T, Tanaka S, Hotta K, Matsuzawa Y, Pratley RE, Tataranni AP. Hypoadiponectine-
mia in obesity and type 2 diabetes: close association with insulin resistance and hyperinsulinemia.
J Clin Endocrinol Metab 2001; 86: 1930–1935.
63. Abbasi F, Chu JW, Mclaughlin T, Lamendola C, Reaven G, Hayden JM, Reaven P. Obesity versus insulin
resistance in modulation of plasma adiponectin concentration. Diabetes 2002; 52(suppl 1): A81.
64. Arita Y, Kihara S, Ouchi N, et al. Paradoxical decrease of an adipose – specific protein, adiponectin,
in obesity. Biochem Biopys Res Commun 1999; 257: 79–83.
65. Hotta K, Funahashi T, Arita Y, et al. Plasma concentration of a novel adipose-specific protein, adi-
ponectin, in type 2 diabetic patients. Arterioscler Thromb Vasc Biol 2000; 20: 1595–1599.
66. Ronti T, Lupattelli G, Mannarino E. The endocrine function of adipose tissue: an update. Clin Endocrinol
(Oxf) 2006; 64: 355–365.
67. Spyridopoulos TN, Petridou E, Skalkidou A, Dessypris N, Chrousos GP, Mantzoros CS. and the Obesity
and Cancer Oncology Group. Low adiponectin levels are associated with renal cell carcinoma:
A case-control study. Int J Cancer 2007; 120: 1573–1578.
120 Blüher and Mantzoros
68. Michalakis K, Williams KJ, Mitsiades N, Blakeman J, Balafouta-Tselenis S, Giannopoulos A, Mantzo-
ros CS. Serum adiponectin concentrations and tissue expression of adiponectin receptors are reduced
in patients with prostate cancer: A case-control study. Cancer Epidemiol Biomarkers Prev 2007; 16:
308–313.
69. Korner A, Pazaitou- Panayiotou K, Kelesidis T, et al. Total and high molecular weight adiponectin in
breast cancer: in vitro and in vivo studies. J Clin Endocrinol Metab 2007; 92: 1041–1048.
70. Tworoger SS, Eliassen AH, Kelesidis T, Colditz GA, Willett WC, Mantzoros CS Hankinson SE, .
Plasma adiponectin concentrations and risk of incident breast cancer J Clin Endocrin Metab 2007; 92:
1510–1516.
71. Kelesidis I, Kelesidis T, Mantzoros CS. Adiponectin and cancer: a systematic review. Br J Cancer 2006;
94: 1221–1225.
72. Yamauchi T, Kamon J, Minokoshi Y, et al. Adiponectin stimulates glucose utilization and fatty-acid
oxidation by activating AMP-activated protein kinase. Nat Med 2002; 8: 1288–1295.
73. Yokota T, Oritani K, Takahashi I, Ishikawa J, Matsuyama A, Ouchi N. Adiponectin, a new member of
the family of soluble defense collagens, negatively regulated the growth of myelmonocytic progenitors
and the functions of macrophages. Blood 2000; 96: 1723–1732.
74. Qi L, van Darn RM, Liu S, Franz M, Mantzoros C, Hu FB. Whole-grain, bran, and cereal fiber intakes
and markers of systemic inflammation in diabetic women. Diabetes Care 2006; 29: 207–211.
75. Qi L, Meigs JB, Liu S, Manson JE, Mantzoros C, Hu FB. Dietary fibers and glycemic load, obesity,
and plasma adiponectin levels in women with type 2 diabetes. Diabetes Care 2006; 29: 1501–1515.
76. Manztoros CS, Williams CJ, Manson JE, Meigs JB, Hu FB. Adherence to the Mediterranean dietary
pattern is positively associated with plasma adiponectin concentrations in diabetic women. Am J Clin
Nutr 2006; 84: 328–335.
77. Monzillo LU, Hamdy O, Horton ES, et al. Effect of lifestyle modification on adipokine levels in obese
subjects with insulin resistance. Obes Res 2003; 11: 1048–1054.
78. Lindsay RS, Funahashi T, Hanson RL, Matsuwaza Y, Tanaka S, Tataranni PA, Knowler WC, Krakoff J. Adi-
ponectin and development of type 2 diabetes in the Pima Indian population. Lancet 2002; 360: 57–58.
79. Bullen J, Bluher S, Kelesidis T, Mantzoros CS. Regulation of adiponectin and its receptors in response to de-
velopment of diet induced obesity in mice. Am J Physiol Endocrinol Metab 2007; 292: E1079–E1086.
80. Blüher S, Bullen J, Mantzoros C. Altered levels of adiponectin and adiponectin receptors may underlie
the effect of ciliary neurotrophic factor (CNTF) to enhance insulin sensitivity in diet induced obese
mice. Horm Metab Res 2008; 40: 225–227.
81. Brennan AM, Mantzoros CS. The role of leptin in human physiology and pathophysiology: emerging
clinical applications in leptin deficient states. Nature (Clinical Practice Endocrinology and Metabolism)
2006; 2: 1–5.
82. Lonnqvist F, Arner P, Nordfors L, Schalling M. Overexpression of the obese (ob) gene in adipose tissue
of human obese subjects. Nat Med 1995; 1: 950–993.
83. Ceddia Rb, William Jr WN, Curi R. Comparing effects of leptin and insulin on glucose metabolism in
skeletal muscle: Evidence for an effect of leptin on glucose uptake and decarboxylation. Int J Obesity
Related Metab Disord 1999; 23: 75–82.
84. Kamohara S, Burcelin R, Halaas JL, Freidman JM. Acute stimulation of glucose metabolism in mice
by leptin treatment. Nature 1997; 389: 374–77.
85. Muoio DM, Dohm GL. Peripheral metabolic actions of leptin. Best Practice Res Clin Endocrinol Metab
2002; 16: 653–66.
86. Clement K, Vaisse C, Lahlou N, et al. A mutation in the human leptin receptor gene causes obesity and
pituitary dysfunction. Nature 1998; 392: 398–401.
87. Farooqui IS, Jebb SA, Langmack G, et al. Effects of recombinant leptin therapy in a child with con-
genital leptin deficiency. N Engl J Med 1999; 341: 879–884.
88. Mantzoros CS, Flier JS. Editorial: Leptin as a therapeutic agent-trials and tribulations. J Clin Endocrinol
Metab 2000; 85: 4000–4002.
89. Oral EA, Simha V, Ruiz E, et al. Leptin replacement therapy for lipodystrophy. N Engl J Med 2002;
346: 57–78.
90. Javor ED, Cochran EK, Musso C, et al. Long-term efficacy of leptin replacement in patients with
generaliszed lipodystrophy. Diabetes 2005; 54: 1994–2002.
Chapter 5 / Insulin Resistance in States of Energy Excess 121
91. Lee JH, Chan JL, Sourlas E, Raptopoulos V, Mantzoros CS. Recombinant methionyl human leptin
therapy in replacement doses improves insulin resistance and metabolic profile in patients with lipoat-
rophy and metabolic syndrome induced by the highly active antiretroviral therapy. J Clin Endocrinol
Metab 2006; 91: 2605–2611.
92. Tsiodras S, Mantzoros C. The role of leptin and adiponectin in the HAART induced metabolic syn-
drome. Am J Infect Dis 2006; 2: 141–152.
93. Santos-Alvarez J, Goberna R, Sanchez-Margalet V. Human leptin stimulates proliferation and activa-
tion of human circulating monocytes. Cell Immunol 1999; 194: 6–11.
94. Giansford T, Willson TA, Metcalf D, et al. Leptin can induce proliferation, differentiation, and func-
tional activation of hemopoietic cells. Proc Natl Acad Sci USA 1996; 93: 14564–14568.
95. Chan JL, Mantzoros CS. Role of leptin in energy-deprivation states: normal human physiology
and clinical implications for hypothalamic amenorrhoea and anorexia nervosa. Lancet 2005; 366:
74–85.
96. Smith SR, Bai F, Charbonneau C, et al. A promoter genotype and oxidative stress potentially link
resistin to human insulin resistance. Diabetes 2003; 52: 1611–1618.
97. Wang H, Chu WS, Hemphill C, Elbein SC. Human resistin gene: molecular scanning and evaluation
of association with insulin sensitivity and type 2 diabetes in Caucasians. J Clin Endocrinol Metab
2002; 87: 2520–2524.
98. Vidal-Puig A, O’Rahilly S, Resistin: a new link between obesity and insulin resistance. Clin Endocrio-
nol (Oxf) 2001; 55: 437–438.
99. Lee JH, Bullen Jr JW, Stoyneva VL, Mantzoros CS. Circulating resistin in lean, obese, and insulin-
resistant mouse models: lack of association with insulinemia and glycemia. Am J Physiol Endocrinol
Metab 2005; 288: E625–E632.
100. Lee JH, Chan JL, Yiannakouris N, et al. Circulating resistin levels are not associated with obesity or
insulin resistance in humans and are not regulated by fasting or leptin administration: cross-sectional
and interventional studies in normal, insulin-resistant, and diabetic subjects. J Clin Endocrinol Metab
2003; 88: 4848–4856.
101. Fukuhara A, Matsuda M, Nishizawa M, et al. Visfatin: a protein secreted by visceral fat that mimics
the effects of insulin. Science 2005; 307: 426–430.
102. Yang Q, Graham TE, Mody N, et al. Serum retinol binding protein 4 contributes to insulin resistance
in obesity and type 2 diabetes. Nature 2005; 21; 436: 356–362.
103. Uzui H, Harpf A, Liu M, et al. Increased expression of membrane type 3-matrix metalloproteinase
in human atherosclerotic plaque: role of activated macrophages and inflammatory cytokines.
Circulation 2002; 106: 3024–3030.
104. Hotamisligil GS, Arner P, Caro JF, et al. Increased adipose tissue expression of tumor necrosis factor-
alpha in human obesity and insulin resistance. J Clin Invest 1995; 95: 2409–1245.
105. Miyazaki Y, Pipek R, Mandarino LJ, DeFronzo RA. Tumor necrosis factor α and insulin resistance
in obese type 2 diabetic patients. Int J Obesity 2003; 27: 88–94.
106. Hotamisligil GS, Peraldi P, Budavari A, et al. IRS-1 mediated inhibition of insulin receptor tyrosine
kinase activity in TNF-α and obesity induced insulin resistance. Science 1996; 271: 665–668.
107. Uysal KT, Wiesbrock SM, Marino MW, Hotamisligil GS. Protection from obesity-induced insulin
resistance in mice lacking TNF-alpha function. Nature 1997; 389: 610–614.
108. Hofmann C, Lorenz K, Braithwaite SS, et al. Altered gene expression for tumor necrosis factor-alpha
and its receptors during drug and dietary modulation of insulin resistance. Endocrinology 1994; 134:
264–270.
109. Sandler S, Bendtzen K, Eizirik DL, Welsh M. Interleukin-6 affects insulin secretion and glucose
metabolism of rat pancreatic islets in vitro. Endocrinology 1990; 126: 1288–1294.
110. Pradhan AD, Manson JE, Rifai N, et al. C-Reative protein, interleukin 6 and the risk of developing
type 2 diabetes. JAMA 2001; 286: 327–334.
111. Pickup JC, Chusney GD, Thomas SM, Burt D. Plasma interleukin 6, tumor necrosis factor and blood
cytokine production in type 2 diabetes. Life Sci 2000; 67: 291–300.
112. Suzuki K, Nakaji S, Yamada M, et al. Systemic inflammatory response to exhaustive exercise. Cytokine
kinetics. Exerc Immunol Rev 2002; 8: 6–48.
113. Starkie R, Ostrowski SR, Jauffred S, et al. Exercise and IL-6 infusion inhibit endotoxin-nduced
122 Blüher and Mantzoros
TNF-alpha production in humans. FASEB J 2003; 17: 884–886.
114. Yudkin JS. Abnormalities of coagulation and fibrinolysis in insulin resistance. Evidence for a common
antecedent? Diabetes Care 1999; 22: C25–C30.
115. Alessi MC, Bastelica D, Morange P, et al. Plasminogen activator inhibitor 1, transforming growth
factor-β1 amd ABMI are closely associated in human adipose tissue during morbid obesity. Diabetes
2000; 49: 1374–1380.
116. Alessi MC, Peiretti F, Morange P, et al. Production of plasminogen activator inhibitor1 by human
adipose tissue: possible link between visceral fat accumulation and vascular disease. Diabetes 1997;
46: 860–867.
6 Targeting Childhood Obesity
Through Lifestyle Modification
Eirini Bathrellou and Mary Yannakoulia
KEY POINTS
• Evidence regarding the efficacy of intervention programs targeting childhood obesity sug-
gests that treatment should focus on dietary and physical activity changes, along with behav-
ior modification and parental support.
• Different types of dietary interventions, aiming at negative energy balance and improvement
of dietary habits, have been applied, such as calorie limit combined with an exchange food
system, low energy balanced diets, or even ad libitum low-glycemic diets.
• The physical activity component includes an increase in structured or nonstructured activities
and a decrease in sedentary activities. To support the child to implement and maintain the
desired lifestyle changes, behavior modification techniques have been incorporated in the
treatment programs, most common of which are self-monitoring, goal setting, stimulus con-
trol, and problem solving.
• Parental involvement is recommended to provide support to the child’s effort, although sev-
eral types of parental roles have been evaluated with variable success.
• Currently no consensus has been reached on the most effective intervention, and most studies
report short-term results with limited generalizability.
• There is an urgent need for well-designed randomized trials to evaluate the long-term effec-
tiveness of lifestyle interventions for the management of children’s overweight.
Key Words: Childhood Obesity, Dietary intake, Physical activity, Behavior modification,
Parental involvement, Low-glycemic diets
1. INTRODUCTION
Childhood obesity has been recognized as a public health priority for many countries.
Prevalence of overweight has increased in Europe, the United States, and many other
parts of the world (1–3). During the last decades, all industrialized and many low-income
countries have doubled or even tripled their numbers, while countries which traditionally
confronted undernutrition problems now encounter obesity problems as well (4). In addi-
tion, comparisons of the distribution of body mass index (BMI) between earlier and later
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_6,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
125
126 Bathrellou and Yannakoulia
Dietary Physical
intake activity
Behavior
Parental support
S o c i a l s u p p o r t
Fig. 1. Interaction of the parameters targeted for the management of children’s overweight.
studies show a greater shift in the upper part of the distribution, implying that heavier
children have now become even heavier (5).
This global epidemic would not have justified the alarming interest of scientists, health
care professionals, and the general public on the prevention and treatment of childhood
obesity, if it were not for its multilevel consequences. Obesity has both short and long-
term health consequences, affecting the child both in its present and future adult life (6).
One of the most well documented short-term effects refers to the cardiovascular risk
factors, namely hypertension, dyslipidemia, endothelial dysfunction, hyperinsulinemia,
and insulin resistance (7–9). Metabolic syndrome, a clustering of cardiovascular risk
factors frequently seen in adults, has also been identified in children and it correlates with
obesity status (10–12). Childhood obesity also has harmful psychosocial and economic
consequences (13,14), and it tracks well into adulthood (15,16).
Even though genetic predisposition and environmental influences interact to cause
excess weight, the accelerated increase in the prevalence of childhood obesity during
the last decades cannot be explained by a genetic shift (17). It rather reflects profound
changes in environmental factors, resulting in positive energy balance. Thus, treatment
should focus on the modifiable factors of the energy equilibrium, i.e., dietary intake
and physical activity. Several approaches have been proposed for inducing dietary and
physical activity changes, along with behavior modification and the participation of
parents (Fig. 1). Purpose of this chapter is to discuss these approaches in the context of
lifestyle interventions in managing overweight in children.
2. DIETARY CHANGES
Although hypocaloric diets have been widely used in achieving weight loss, the opti-
mal type of diet remains unknown. Research in adults indicates that short-term success
can be achieved with diets varying widely in composition, from very low-fat to very
low-carbohydrate content; however, most individuals experience weight regain over the
long term (18–21). In children, combinations of calorie limits and food exchange sys-
tems have been applied. The traffic light diet is a food exchange system, first developed
by Epstein and colleagues (22); foods are divided into three categories according to their
energy and fat content: greens can be consumed freely, oranges should be consumed
Chapter 6 / Targeting Childhood Obesity Through Lifestyle Modification 127
with caution, and reds should be avoided. A daily or weekly number of servings for
each of these food groups is, then, recommended. The traffic light diet has evolved in
terms of number of calories or red foods (23), allowing for a higher calorie limit (up to
1,500 kcal) and more red foods (24), while modified versions have been developed using
either a specific diet (25,26) or no calorie limit (27).
A low energy diet, ranging in calorie content from 1,200 to 2,000 kcal, applied either as
a tailored or an exchange-based regime, has been also used (25,28–32). Most of the recom-
mended diets so far were characterized as “prudent” or “balanced,” with a caloric deficit of
around 30% less of the reported intake or 15% less than the estimated required intake, provid-
ing approximately 30% of calories from fat. However, available evidence from randomized
trials do not support current recommendations for low-fat energy restricted diets (33).
Less restrictive dietary interventions have been successfully undertaken. Recent
guidelines suggest that dietary treatment should focus on eating behaviors, such as break-
fast skipping and meal frequency, eating out and portion size (34), rather than calorie
restriction per se. The need for putting less restraint in the dietary manipulation is also
supported by evidence indicating that flexible, not rigid, dietary restraint is associated
with lower BMI values and a more successful long-term weight control, both in adults
and children (35,36), as well as by concerns that obese children are at high risk for
developing eating disorders or show resistance to treatment (37). Under this perspective,
nonprescription approaches, promoting the concept of “eating differently, not necessarily
less” and a healthy eating (38,39), or focusing on ad libitum low-glycemic diets have
been investigated. With regard to the latter, Ebbeling et al. examined the long-term
effects of a reduced glycemic load, nonenergy restricted diet with those of a reduced-fat,
externally imposed hypocaloric diet, in a small-scale randomized controlled trial of 16
obese adolescents (40). Over 12 months, BMI and fat mass significantly decreased in the
reduced-glycemic load diet group, whereas neither measure changed significantly in the
conventional diet group. Furthermore, insulin resistance, as assessed by the homeostasis
model assessment, increased less with the low-glycemic load diet, even after statistical
adjustment for BMI. These findings indicate that reducing the glycemic load or index of
a diet, without externally imposing energy restriction, may yield several health benefits
in young people. Adolescents, in particular, may more easily adhere to such a dietary
pattern, as they may feel less hungry and also more flexible in their dietary choices, thus
reaching more easily a negative energy balance allowing for a weight loss.
3. PHYSICAL ACTIVITY INTERVENTIONS
Including a physical activity-related component in weight management programs for
overweight children is of major importance, because of its obvious effect on energy
balance and its beneficial impact on cardiovascular risk factors, even independently of
weight reduction (41,42). Recommendations regarding physical activity in children tar-
get a generally active lifestyle, and suggest at least 60 min of moderate intensity physical
activity, if possible everyday, and not exceeding 2 h of daily screen time (34). Within
school setting, individual or team noncompetitive sports, and recreational activities are
suggested (43), as well as an active participation in physical education classes (44).
Results of a 10-year follow up suggest that physical activity as a lifestyle change is a
promising, feasible, and convenient way for managing overweight in children (45). On the
one hand, both structured and nonstructured activities have been beneficial in reducing BMI
128 Bathrellou and Yannakoulia
in children (46). On the other hand, targeting sedentary activities has been proven at least
as (47) or even more (48) effective in reducing percent overweight in children compared
with targeting an increase in physical activity per se. It has, further, been proposed that
changes in physical activity habits in children reach a plateau: a set-point of physical
activity competence may exist within each child, irrespective of the environmental
opportunities (49), acting as a mediator of his/her physical activity levels.
4. BEHAVIOR MODIFICATION
Both dietary intake and physical activity constitute the result of numerous corre-
sponding behaviors; therefore, studying behavior in the context of combating obesity
has attracted great scientific interest. The beneficial effect of adding behavioral modi-
fication techniques in a conventional program for the treatment of childhood obesity
has been originally described in the early 1990s (50,51), and has been confirmed many
times ever since (52). Behavioral and cognitive-behavioral components have been
considered as important components of the lifestyle treatment programs (53). There is
also some preliminary evidence proposing that the use of a motivational interviewing
style by pediatricians and dietitians may be another promising office-based strategy for
preventing overweight children to become obese (54), even though its efficacy as a treatment
modality has not been proven yet (55).
Several techniques have been used in the childhood obesity treatment programs under
the aim of modifying eating patterns and increasing physical activity levels. These include
contracting, self-monitoring, stimulus control, goal setting, reinforcement, parental training,
homework exercises, problem solving, and overcoming stressful situations. Although
it is difficult to isolate a specific technique and assess its effectiveness, some of them
have been evaluated and proven to have a beneficial effect in pediatric populations,
like self-monitoring (56), stimulus control (57), and problem-solving (58).
5. THE ROLE OF PARENTS
Parents affect children’s eating and physical activity patterns by several means,
namely formulating children’s environment, being role models, and controlling their
dietary intake (59). Parental participation is considered as an essential component in
a program aiming at modifying child’s lifestyle habits and combating obesity. A great
body of research investigates the most effective parental role. Epstein and colleagues
highly supported the role of parents as targets for managing their own weight along
with their child’s effort to manage body weight (45): a significantly higher reduction
in percent overweight of children was revealed after 10 years of follow-up when par-
ents and children were both targeted for weight loss compared to when only children
were targeted. Israel et al. found that when parents were helpers, rather than cotargets,
the therapeutic outcome was slightly enhanced (60). Moreover, training children in
self-regulatory techniques compared with assigning parents most responsibility for
change was proven essential in maintaining percent overweight loss after treatment
(29). In the studies of Golan and colleagues, parents were the exclusive agents of
change, without any direct child involvement (61). It was found that this approach was
more efficient in managing children’s weight compared with the approach of children
being the exclusive agents.
Chapter 6 / Targeting Childhood Obesity Through Lifestyle Modification 129
As studies are not conclusive with regard to the most effective parental role or the
exact degree of parental involvement, recommendations so far suggest a rather supportive
role of parents, with less involvement as the child gets older (17), and this is the most
widely adopted approach (25,32,39,62,63).
6. IMPLEMENTATION OF PROGRAMS
The structure of the programs targeting childhood obesity varies greatly. In most
cases, therapeutic programs are conducted in groups (25,60,62–65), and seldom in
individual sessions (28,39) or in conjunction (38,57). Although data comparing indi-
vidualized and group treatment are scarce, there seems to be a slight advantage in favor
of the group format. Goldfield et al. (66) compared the effectiveness of the same family-
based behavioral treatment conducted only in groups or in a mixed format, combining
group and individualized sessions. As weight outcomes did not differ between the two
approaches, group only format was proven more cost-effective. Moreover, Braet and
Van Winckel (39) found a favorable long-term tendency for the group approach, when it
was compared with an individualized, and to a summer camp approach. Diverging from
the conventional setup, and in the context of applying a more cost-effective approach
with greater generalization and dissemination, innovative delivery approaches using
media technologies have also been evaluated. Frequent telephone and mail contact were
proven feasible and effective in promoting use of behavioral skills for weight control in
a group of adolescents, when compared with a single-advice typical care session (67).
An interactive Website-based behavioral treatment was effective in improving some
weight-related parameters in the short term, but Web hits decreased dramatically in the
long-term (68).
The length of the intervention ranges from 6 weeks to 18 months, with the majority of
studies lasting between 3 and 6 months (23). Sessions are usually conducted on a weekly
basis. Combinations of weekly and biweekly (29) or even monthly (45) sessions has also
been applied, lengthening intervention time. As long-term effectiveness is the ultimate
outcome of obesity interventions, addressing weight loss maintenance postinterventionally
emerges as a necessity, in accordance to adult studies which, in this regard, propose the
extension of treatment contact or content (69). Wilfley et al. (70) successfully tested
the efficacy of adding an active maintenance phase following a standard family-based
behavioral treatment, in a randomized controlled trial. Interestingly, both maintenance
methods studied, i.e., behavioral skills or social facilitation, produced many benefits, either
in weight or psychosocial outcomes, compared with no maintenance approach. Still, a
decline in treatment effectiveness was observed, regardless of the treatment duration or content,
suggesting the need for the development of continuous care models for children.
7. CONCLUDING REMARKS
As the degree of obesity of children who participate in weight control programs has
increased over the last two decades, in accordance to the increase in childhood obesity
rates observed in the general population, it is not surprising that more children in the
earlier studies were below the criteria for being at risk for overweight or overweight
after treatment (71). As young people nowadays live in a more obesogenic environment,
promoting greater food intake and more sedentary activities, contemporary programs
130 Bathrellou and Yannakoulia
need to be more powerful to produce treatment effects similar to those observed in the
studies during 1970s and 1980s.
A lot of work needs to be done in refining existing programs. An earlier review
concluded that the reduction of sedentary behavior appeared to be the most effective
intervention for achieving and maintaining weight loss in children and that the degree
of parental involvement in childhood obesity interventions remains uncertain (72). A
more recent pointed out that, although the combination of diet, exercise, behavioral
techniques, and parental involvement remains the cornerstone for improving the effec-
tiveness of a weight-loss program, there is still a limited number of studies including a
control group (73). Furthermore, most studies are small and noncomparable, they report
short-term results with limited generalizability, rarely reporting health outcomes, such
as cardiovascular risk factors (74). With regard to diet, interventions including dietetic
treatment can be effective, but there are not many quality studies undertaken to date,
with adequate long-term follow-up data (23). Therefore, there is an urgent need for well-
designed randomized trials to evaluate the lasting effectiveness of dietary interventions
(33) and lifestyle programs.
In conclusion, for the time being, the combination of the four parameters discussed,
i.e., dietary and physical activity changes, behavioral modification and parental support,
constitute the best available therapeutic strategy for childhood obesity. The most recent
recommendations on the treatment of childhood obesity are based on this scheme (34),
proposed though to be implemented at different settings, from a primary care provider to a
multidisciplinary team, and supplemented when needed with more invasive strategies.
REFERENCES
1. Ebbeling, C.B., D.B. Pawlak, and D.S. Ludwig. Childhood obesity: public-health crisis, common sense
cure. Lancet, 2002, 360(9331): p. 473–82.
2. Jackson-Leach, R. and T. Lobstein. Estimated burden of paediatric obesity and co-morbidities in Europe.
Part 1. The increase in the prevalence of child obesity in Europe is itself increasing. Int J Pediatr Obes,
2006, 1(1): p. 26–32.
3. Ogden, C.L., et al. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA, 2006,
295(13): p. 1549–55.
4. Wang, Y. and T. Lobstein. Worldwide trends in childhood overweight and obesity. Int J Pediatr Obes,
2006, 1(1): p. 11–25.
5. Flegal, K.M. and R.P. Troiano. Changes in the distribution of body mass index of adults and children
in the US population. Int J Obes Relat Metab Disord, 2000, 24(7): p. 807–18.
6. Reilly, J.J., et al. Health consequences of obesity. Arch Dis Child, 2003, 88(9): p. 748–52.
7. Freedman, D.S., et al. The relation of overweight to cardiovascular risk factors among children and
adolescents: the Bogalusa Heart Study. Pediatrics, 1999, 103(6 Pt 1): p. 1175–82.
8. Giannini, C., et al. Obese related effects of inflammatory markers and insulin resistance on increased
carotid intima media thickness in pre-pubertal children. Atherosclerosis, 2008, 197(1): p. 448–56.
9. Valle Jimenez, M., et al. Endothelial dysfunction is related to insulin resistance and inflammatory
biomarker levels in obese prepubertal children. Eur J Endocrinol, 2007, 156(4): p. 497–502.
10. Weiss, R., et al. Obesity and the metabolic syndrome in children and adolescents. N Engl J Med, 2004,
350(23): p. 2362–74.
11. Invitti, C., et al. Metabolic syndrome in obese Caucasian children: prevalence using WHO-derived
criteria and association with nontraditional cardiovascular risk factors. Int J Obes (Lond), 2006, 30(4):
p. 627–33.
12. Pervanidou, P., C. Kanaka-Gantenbein, and G.P. Chrousos. Assessment of metabolic profile in a clinical
setting. Curr Opin Clin Nutr Metab Care, 2006, 9(5): p. 589–95.
Chapter 6 / Targeting Childhood Obesity Through Lifestyle Modification 131
13. Strauss, R.S. and H.A. Pollack. Social marginalization of overweight children. Arch Pediatr Adolesc
Med, 2003, 157(8): p. 746–52.
14. Wang, G. and W.H. Dietz. Economic burden of obesity in youths aged 6 to 17 years: 1979–1999.
Pediatrics, 2002, 109(5): p. E81–1.
15. Whitaker, R.C., et al. Predicting obesity in young adulthood from childhood and parental obesity. N
Engl J Med, 1997, 337(13): p. 869–73.
16. Deshmukh-Taskar, P., et al. Tracking of overweight status from childhood to young adulthood: the
Bogalusa Heart Study. Eur J Clin Nutr, 2006, 60(1): p. 48–57.
17. Barlow, S.E. Expert committee recommendations regarding the prevention, assessment, and treatment
of child and adolescent overweight and obesity: summary report. Pediatrics, 2007, 120(Suppl 4): p.
S164–92.
18. Baron, J.A., et al. A randomized controlled trial of low carbohydrate and low fat/high fiber diets for
weight loss. Am J Public Health, 1986, 76(11): p. 1293–6.
19. McManus, K., L. Antinoro, and F. Sacks. A randomized controlled trial of a moderate-fat, low-energy
diet compared with a low fat, low-energy diet for weight loss in overweight adults. Int J Obes Relat
Metab Disord, 2001, 25(10): p. 1503–11.
20. Foster, G.D., et al. A randomized trial of a low-carbohydrate diet for obesity. N Engl J Med, 2003,
348(21): p. 2082–90.
21. Stern, L., et al. The effects of low-carbohydrate versus conventional weight loss diets in severely obese
adults: one-year follow-up of a randomized trial. Ann Intern Med, 2004, 140(10): p. 778–85.
22. Epstein, L.H., et al. Child and parent weight loss in family-based behavior modification programs.
J Consult Clin Psychol, 1981, 49(5): p. 674–85.
23. Collins, C.E., et al. Measuring effectiveness of dietetic interventions in child obesity: a systematic
review of randomized trials. Arch Pediatr Adolesc Med, 2006, 160(9): p. 906–22.
24. Epstein, L.H., et al. The effect of reinforcement or stimulus control to reduce sedentary behavior in the
treatment of pediatric obesity. Health Psychol, 2004, 23(4): p. 371–80.
25. Reinehr, T., et al. Long-term follow-up of overweight children: after training, after a single consultation
session, and without treatment. J Pediatr Gastroenterol Nutr, 2003, 37(1): p. 72–4.
26. Jiang, J.X., et al. A two year family based behaviour treatment for obese children. Arch Dis Child,
2005, 90(12): p. 1235–8.
27. Duffy, G. and S.H. Spence. The effectiveness of cognitive self-management as an adjunct to a behav-
ioural intervention for childhood obesity: a research note. J Child Psychol Psychiatry, 1993, 34(6): p.
1043–50.
28. Flodmark, C.E., et al. Prevention of progression to severe obesity in a group of obese schoolchildren
treated with family therapy. Pediatrics, 1993, 91(5): p. 880–4.
29. Israel, A.C., et al. An evaluation of enhanced self-regulation training in the treatment of childhood
obesity. J Pediatr Psychol, 1994, 19(6): p. 737–49.
30. Golan, M., et al. Parents as the exclusive agents of change in the treatment of childhood obesity. Am
J Clin Nutr, 1998, 67(6): p. 1130–5.
31. Eliakim, A., et al. The effect of a combined intervention on body mass index and fitness in obese chil-
dren and adolescents – a clinical experience. Eur J Pediatr, 2002, 161(8): p. 449–54.
32. Nemet, D., et al. Short- and long-term beneficial effects of a combined dietary-behavioral-physical
activity intervention for the treatment of childhood obesity. Pediatrics, 2005, 115(4): p. e443–9.
33. Gibson, L.J., et al. Lack of evidence on diets for obesity for children: a systematic review. Int J Epide-
miol, 2006, 35(6): p. 1544–52.
34. Spear, B.A., et al. Recommendations for treatment of child and adolescent overweight and obesity.
Pediatrics, 2007, 120(Suppl 4): p. S254–88.
35. Westenhoefer, J. Establishing dietary habits during childhood for long-term weight control. Ann Nutr
Metab, 2002, 46(Suppl 1): p. 18–23.
36. Westenhoefer, J., A.J. Stunkard, and V. Pudel. Validation of the flexible and rigid control dimensions
of dietary restraint. Int J Eat Disord, 1999, 26(1): p. 53–64.
37. Decaluwe, V. and C. Braet. The cognitive behavioural model for eating disorders: a direct evaluation
in children and adolescents with obesity. Eat Behav, 2005, 6(3): p. 211–20.
38. Braet, C. Treatment of obese children: a new rationale. Clin Child Psychol Psychiatry, 1999, 4: p.
579–591.
132 Bathrellou and Yannakoulia
39. Braet, C. and M. Van Winckel. Long-term follow-up of a cognitive behavioral treatment program for
obese children. Behav Ther, 2000, 31: p. 55–74.
40. Ebbeling, C.B., et al. A reduced-glycemic load diet in the treatment of adolescent obesity. Arch Pediatr
Adolesc Med, 2003, 157(8): p. 773–9.
41. Nassis, G.P., et al. Aerobic exercise training improves insulin sensitivity without changes in body
weight, body fat, adiponectin, and inflammatory markers in overweight and obese girls. Metabolism,
2005, 54(11): p. 1472–9.
42. Meyer, A.A., et al. Improvement of early vascular changes and cardiovascular risk factors in obese
children after a six-month exercise program. J Am Coll Cardiol, 2006, 48(9): p. 1865–70.
43. American Academy of Pediatrics. Physical fitness and activity in schools. Pediatrics, 2000, 105(5):
p. 1156–7.
44. Carrel, A.L., et al. Improvement of fitness, body composition, and insulin sensitivity in overweight
children in a school-based exercise program: a randomized, controlled study. Arch Pediatr Adolesc
Med, 2005, 159(10): p. 963–8.
45. Epstein, L.H., et al. Ten-year follow-up of behavioral, family-based treatment for obese children. JAMA,
1990, 264(19): p. 2519–23.
46. Berkey, C.S., et al. One-year changes in activity and in inactivity among 10- to 15-year-old boys and
girls: relationship to change in body mass index. Pediatrics, 2003, 111(4 Pt 1): p. 836–43.
47. Epstein, L.H., et al. Decreasing sedentary behaviors in treating pediatric obesity. Arch Pediatr Adolesc
Med, 2000, 154(3): p. 220–6.
48. Epstein, L.H., et al. Effects of decreasing sedentary behavior and increasing activity on weight change
in obese children. Health Psychol, 1995, 14(2): p. 109–15.
49. Wilkin, T.J., et al. Variation in physical activity lies with the child, not his environment: evidence for
an ‘activitystat’ in young children (EarlyBird 16). Int J Obes (Lond), 2006, 30(7): p. 1050–5.
50. Epstein, L.H., et al. Comparison of family-based behavior modification and nutrition education for
childhood obesity. J Pediatr Psychol, 1980, 5(1): p. 25–36.
51. Epstein, L.H., et al. Effects of family-based behavioral treatment on obese 5-to-8-year-old children.
Behavior Therapy, 1985, 16: p. 205–212.
52. Jelalian, E. and B.E. Saelens. Empirically supported treatments in pediatric psychology: pediatric
obesity. J Pediatr Psychol, 1999, 24(3): p. 223–48.
53. Powers, S.W., J.S. Jones, and B.A. Jones. Behavioral and cognitive-behavioral interventions with
pediatric populations. Clin Child Psychol Psychiatry, 2005, 10(1): p. 65–77.
54. Schwartz, R.P., et al. Office-based motivational interviewing to prevent childhood obesity: a feasibility
study. Arch Pediatr Adolesc Med, 2007, 161(5): p. 495–501.
55. Resnicow, K., R. Davis, and S. Rollnick. Motivational interviewing for pediatric obesity: Conceptual
issues and evidence review. J Am Diet Assoc, 2006, 106(12): p. 2024–33.
56. Kirschenbaum, D.S., J.N. Germann, and B.H. Rich. Treatment of morbid obesity in low-income ado-
lescents: effects of parental self-monitoring. Obes Res, 2005, 13(9): p. 1527–9.
57. Golan, M., M. Fainaru, and A. Weizman. Role of behaviour modification in the treatment of childhood
obesity with the parents as the exclusive agents of change. Int J Obes Relat Metab Disord, 1998, 22(12):
p. 1217–24.
58. Graves, T., A.W. Meyers, and L. Clark. An evaluation of parental problem-solving training in the
behavioral treatment of childhood obesity. J Consult Clin Psychol, 1988, 56(2): p. 246–50.
59. Johnson-Taylor, W.L. and J.E. Everhart. Modifiable environmental and behavioral determinants of
overweight among children and adolescents: report of a workshop. Obesity (Silver Spring), 2006, 14(6):
p. 929–66.
60. Israel, A.C., L.C. Solotar, and E. Zimand. An investigation of two parental involvement roles in the
treatment of obese children. Int J Eat Disord, 1990, 9: p. 557–564.
61. Golan, M. and S. Crow. Targeting parents exclusively in the treatment of childhood obesity: long-term
results. Obes Res, 2004, 12(2): p. 357–61.
62. Levine, M.D., et al. Is family-based behavioral weight control appropriate for severe pediatric obesity?
Int J Eat Disord, 2001, 30(3): p. 318–28.
63. Korsten-Reck, U., et al. Freiburg Intervention Trial for Obese Children (FITOC): results of a clinical
observation study. Int J Obes (Lond), 2005, 29(4): p. 356–61.
Chapter 6 / Targeting Childhood Obesity Through Lifestyle Modification 133
64. Brownell, K.D., J.H. Kelman, and A.J. Stunkard. Treatment of obese children with and without their
mothers: changes in weight and blood pressure. Pediatrics, 1983, 71(4): p. 515–23.
65. Epstein, L.H., J.N. Roemmich, and H.A. Raynor. Behavioral therapy in the treatment of pediatric obes-
ity. Pediatr Clin North Am, 2001, 48(4): p. 981–93.
66. Goldfield, G.S., et al. Cost-effectiveness of group and mixed family-based treatment for childhood
obesity. Int J Obes Relat Metab Disord, 2001, 25(12): p. 1843–9.
67. Saelens, B.E., et al. Behavioral weight control for overweight adolescents initiated in primary care.
Obes Res, 2002, 10(1): p. 22–32.
68. Williamson, D.A., et al. Two-year internet-based randomized controlled trial for weight loss in African-
American girls. Obesity (Silver Spring), 2006, 14(7): p. 1231–43.
69. Jeffery, R.W., et al. Long-term maintenance of weight loss: current status. Health Psychol, 2000, 19(1
Suppl): p. 5–16.
70. Wilfley, D.E., et al. Efficacy of maintenance treatment approaches for childhood overweight: a rand-
omized controlled trial. JAMA, 2007, 298(14): p. 1661–73.
71. Epstein, L.H., et al. Family-based obesity treatment, then and now: twenty-five years of pediatric obesity
treatment. Health Psychol, 2007, 26(4): p. 381–91.
72. Glenny, A.M., et al. The treatment and prevention of obesity: a systematic review of the literature. Int
J Obes Relat Metab Disord, 1997, 21(9): p. 715–37.
73. Snethen, J.A., M.E. Broome, and S.E. Cashin. Effective weight loss for overweight children: a meta-
analysis of intervention studies. J Pediatr Nurs, 2006, 21(1): p. 45–56.
74. Whitlock, E.P., et al. Screening and interventions for childhood overweight: a summary of evidence
for the US Preventive Services Task Force. Pediatrics, 2005, 116(1): p. e125–44.
7 Diet and Physical Activity in the
Prevention of Obesity
Frank B. Hu
KEY POINTS
• Numerous epidemiologic and clinical studies have examined the role of dietary factors in the
development of obesity.
• Cumulative evidence indicates that there is no “magic bullet” for weight control. Rather,
many individual dietary factors each exert a modest effect on body weight, and over time
cumulative effects of small changes in daily energy balance lead to weight gain and obesity.
• On the one hand, there is some evidence that higher consumption of whole grains, fruits, and
vegetables is beneficial for weight control. On the other hand, higher intake of sugar-sweet-
ened beverages is associated with both weight gain and type 2 diabetes risk.
• Emerging evidence suggests potential weight control benefits by lowering refined carbohy-
drates and glycemic loads, but prospective data are limited.
• Epidemiologic studies have provided strong evidence that sedentary such as prolonged TV
watching is an important risk factor for obesity and type 2 diabetes, whereas increasing physi-
cal activity including brisk walking is associated with weight maintenance and a lower risk
of obesity and type 2 diabetes.
• Given the obesogenic environment in which we live, characterized by the abundance of
energy dense, processed and highly convenient foods, and sedentary lifestyle, it is critical to
change our nutrition and physical activity environment and social norms. Otherwise, the
effects of any kind of weight loss or maintenance diets are difficult to sustain.
Key Words: Obesity, Weight loss, Diet, Exercise, Fat, Carbohydrate, Protein, Whole
grains, Fruits andvegetables, Glycemic load
Obesity has reached epidemic proportions in the US. On the basis of the NHANES
2003–2004 data, the prevalence of the conditions in US adults is estimated at 66.3
and 32.2%, respectively (1). The prevalence of morbid obesity (BMI > 40 kg/m2) is
approximately 4.8%. There has been a marked upward trend in obesity over the past
several decades in both men and women.
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_7,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
135
136 Hu
Overweight and obesity are central to the metabolic syndrome and the single most
important risk factor for type 2 diabetes. Obesity is associated with increased incidence
of cardiovascular disease, cancer, and mortality from all-causes. The US Surgeon General
in 2001 issued a Call to Action, pointing out that “Overweight and obesity may soon
cause as much preventable disease and death as cigarette smoking” in the United States.
Approximately 300,000 US deaths a year currently are associated with obesity and
overweight (compared with more than 400,000 deaths a year associated with cigarette
smoking) (2).
Obesity is a complex problem resulting from a combination of genetic, behavioral,
environmental, cultural, and socioeconomic influences. Although behavioral and en-
vironmental factors are considered primary determinants of obesity, specific dietary
lifestyle factors have not been clearly defined. In this chapter, we review epidemiologic
and clinical evidence regarding dietary factors and several popular diets and their effects
on obesity and weight loss. Also we review epidemiologic evidence regarding the role
of physical activity in preventing weight gain.
1. DIETARY FAT
Hypothetically, as dietary fat is the most energy-dense macronutrient in the diet, over-
consumption of energy could result if food intake is not regulated (3). In addition, the
enhanced palatability of high-fat foods could impact regulation of the volume of food
intake, leading to increased energy intake and weight gain. Findings from short-term
feeding studies have also suggested that as carbohydrate produces a greater thermogenic
effect than fat, dietary fat might be used more efficiently and accumulate as body fat
(4). However, when studies are extended to 4 days, no differences in stored energy is
observed, which would not be the case if fat truly is being used more efficiently rela-
tive to carbohydrate. Over 20 years ago, Flatt (5) proposed that carbohydrate intake is
regulated, unlike fat, therefore individuals on high-fat diets in theory consume more
energy than those on low-fat diets to obtain required amounts of carbohydrate. To date,
few data exist that support these claims, and the hypothesis itself is flawed since excess
carbohydrate intake can be converted to fat, which is then stored (3).
Although several cross-sectional studies suggested a positive association between
dietary fat intake and obesity, few prospective cohort studies have examined long-term
relationships between dietary fat and body fatness or weight gain, and among those that
have, the results have been highly inconsistent (6,7). These studies have varied consid-
erably in size, duration of follow-up, age groups, covariates adjusted in the statistical
analyses, and dietary assessment methods.
In a 6-year study of 361 Swedish women, Heitmann and colleagues (8) found a
significant association between high dietary fat intake and BMI in predisposed women
(P = 0.003) but not obese women with lean parents or lean women with or without
obese parents. There was a relationship between dietary fat and BMI in genetically
predisposed women after adjustment for total energy intake, smoking habits, physical
activity, and menopausal status, but subgroup analysis was limited by the very small
sample size (n = 56).
A much larger study by Field and colleagues (9) examined the association between
dietary fat and 8-year weight gain among 41,518 women in the Nurses’ Health Study
Chapter 7 / Diet and Physical Activity in the Prevention of Obesity 137
(NHS). Data showed a positive relationship between weight change and increased intake
of animal fat, saturated fat, and trans fat, especially in overweight women. There was a
weak positive association between total fat consumption and weight gain, no associa-
tion with increases in percentages of energy from mono or polyunsaturated fats, and
no evidence that parental weight status modified the relationship between dietary fat
and weight gain. The effects of fat on body weight vary according to type of fat. These
differences may reflect biological actions of these fats on insulin resistance and fat ac-
cumulation. In that the amount of energy provided by different types of fat is the same,
the varied effects may also reflect confounding of the association between diet and body
weight by other dietary and lifestyle factors.
Only one prospective study (of 16, 587 US men aged 40–75 in the Health Profes-
sionals’ Follow-up Study) has examined the association between dietary fat intake and
9-year change in waist circumference. Multivariate analyses by Koh-Banerjee and col-
leagues (10) found that total fat intake was not associated with gain in waist circumfer-
ence. However, a significant association was found between increasing consumption of
trans fat and gain in waist circumference, even after further adjustment for concurrent
changes in BMI. Although confounding by other dietary factors related to high intake
of trans fat (e.g., fast-food and breakfast habits) cannot be ruled out, these data suggest
potentially detrimental effects of trans fat on fat accumulation.
1.1. Low-Fat Diets and Weight Loss
To date, a large spectrum of randomized trials have been published that offer a less
confounded evaluation of low-fat diets in relation to body weight than the many ecologic
and cross-sectional studies that have examined this association (see review by Malik and
Hu (11)). A metaanalysis (12) of 28 short-term trials suggests that a 10% decrease in total
energy from fat can reduce bodyweight by 16 g/day, which is extrapolated to a weight
reduction of 8.8 kg by 18 months and 23.4 kg by 4 years (3). Longer-term trials, how-
ever, do not substantiate these predictions. In a qualitative review by Willett (3), several
clinical and intervention trials of the effect of low-fat diets (ranging from 18 to 40% of
energy) on weight, including nine long-term trials ranging from 12 to 24 months, were
evaluated. This review suggests that diets lower in fat can result in modest reductions in
body weight in the short-term but studies lasting for 1 year or more show that 18–40% of
energy intake from fat has a negligible effect on body weight (3).
Similar findings were observed in the Women’s Health Initiative Dietary Modification
Trial (WHI) (13), a randomized intervention trial comparing an ad libitum low-fat di-
etary pattern with usual diet in 48,835 postmenopausal women in the US with a mean
follow-up of 7.5 years. The intervention group was instructed to reduce total fat intake
to 20% of total energy intake by increasing fruit, vegetable, and whole grain consump-
tion, and received intensive behavioral modification sessions led by nutritionists. The
control group received a copy of Dietary Guidelines for Americans (14) and followed
their usual diet. Neither group was given instructions to lose weight. Overall results
suggested that although the intervention group lost weight in the first year compared
with the control group (2.2 kg; P < 0.01), the difference in weight loss between the
two groups was negligible at the end of follow-up (year 9) over an average of 7.5 years
(0.4 kg at 7.5 years; Fig. 1) (13).The authors suggest the trial provides evidence that fat
restriction does not lead to weight gain, refuting claims that low-fat, high-carbohydrate
138 Hu
Age 50-59, y Age 60-69, y Age 70-79, y
4
3 Control
Intervention
Mean Difference, kg
2
1
0
–1
–2
–3
–4
0 1‡ 2‡ 3‡ 4‡‡ 5‡ 6‡ 7‡ 8† 9 0 1‡ 2‡ 3‡ 4‡ 5‡ 6‡ 7‡ 8‡ 9† 0 1‡ 2‡ 3‡ 4‡ 5‡ 6‡ 7∗ 8 9
Years of Intervention Years of Intervention Years of Intervention
Fig. 1. Differences from baseline in body weight by low-fat diet vs. usual diet, and age at screen-
ing. The error bars indicate 95% CIs. Numbers at baseline for intervention and control in the
50- to 59-year group were 7,206 and 10,797, respectively; 60–69 years, 9,086 and 13,626; 70–79
years, 3,249 and 4,871. Adapted from (13).
diets are driving the obesity trend (13).However, few older women are supposed to gain
weight. A major limitation of the study was that the authors did not differentiate between
types of fats and carbohydrates.
2. DIETARY CARBOHYDRATES
Low-fat, high-carbohydrate diets generally produce higher postprandial glucose
and insulin responses. However, similar to total fat, the total percentage of energy
derived from carbohydrates in the diet has generally not been found to predict dia-
betes risk. Metabolic consequences of carbohydrate intake depend not only on their
quantity but also on their quality. The glycemic response of a given carbohydrate load
depends on the food sources, which has led to the development of the glycemic index
(GI), ranking foods by their ability to raise postprandial blood glucose levels (15).
The GI quantifies the glycemic response by a standard amount of carbohydrates from
a food relative to the response by the same amount of carbohydrates from white bread
or glucose. The overall GI of a diet has been found to be associated with an increased
diabetes risk in some prospective observational studies (16). However, the relevance
of the concept of GI is indirectly supported by the reduction in diabetes incidence
observed with acarbose, an alpha-glucosidase inhibitor that slows down the digestion
of carbohydrates (17).
Effects of carbohydrate-rich foods on insulin resistance and diabetes risk may also
depend on fiber content and type. Several epidemiologic studies found that diets rich in
whole grains or cereal fiber may protect against type 2 diabetes (16). Controlled feed-
ing studies have found benefits of whole grains, when compared with refined grains,
on insulin sensitivity and glucose metabolism. This effect may be partially mediated
by positive effects on body weight – studies generally support an inverse association
between intake of whole grains and body weight (18). In addition, fiber tends to slow
down gastrointestinal absorption, resulting in a lower GI of whole-grain products com-
pared with their refined-grain counterparts, but other mechanisms by which whole grains
influence glucose metabolism are likely to play a role as well, e.g., short-chain fatty acid
production and micronutrient content.
Chapter 7 / Diet and Physical Activity in the Prevention of Obesity 139
a Weighted Mean
Difference, kg Favors Favors
b Weighted Mean
Difference, kg Favors Favors
(95% CI) % Weight Low Carb Low Fat (95% CI) % Weight Low Carb Low Fat
18 19
Brehm et al, 2003 –4.0 (–6.6 to –1.4) 20.2 Foster et al, 2003 –2.8 (–6.5 to 0.9) 27.4
19 21
Foster et al, 2003 –3.7 (–6.6 to –0.8) 18.2 Stern et al, 2004 –2.0 (–5.0 to 1.0) 34.6
20 23
Samaha et al, 2003 –3.9 (–6.2 to –1.57) 21.5 Dansinger et al, 2005 1.2 (–1.5 to 3.9) 38.0
22
Yancy et al, 2004 –5.5 (–8.1 to –2.9) 20.0
23
Dansinger et al, 2005 0.4 (–2.2 to 3.0) 20.1
Overall (95% CI) –3.3 (–5.3 to –1.4) Overall (95% CI) –1.0 (–3.5 to 1.5)
Heterogeneity P = .02 Heterogeneity P = .15
2 –9 –6 –3 0 3 6 9 2 –9 –6 –3 0 3 6 9
Inconsistency I =65% Inconsistency I = 48%
Weighted Mean Difference, kg Weighted Mean Difference, kg
(95% UI, 7%-87%) (95% UI, 0%-85%)
Fig. 2. Weighted mean differences in weight loss after (a) 6 months and (b) 12 months of follow-
up from a metaanalysis (30) comparing the effects of ad libitum low-carbohydrate diets versus
low-fat energy-restricted diets on weight loss. Adapted from (19).
2.1. Low-Carbohydrate Diets
Given the vast popularity of low-carbohydrate diets, a large number of studies, mostly
randomized controlled trials, have been conducted to evaluate the efficacy of carbohy-
drate-restricted diets compared with fat-restricted diets on weight loss. A metaanalysis
(19) compared the effects of ad libitum low-carbohydrate diets (allowing a maximum
intake of 60 g of carbohydrates per day or 10% energy) with those of low-fat ( 30%
energy), energy-restricted diets on weight loss (19). In total, five randomized controlled
trials (n = 447) were analyzed, with 6–12 months follow-up. The authors found that after
6 months, participants randomized to a low-carbohydrate diet had lost more weight than
those randomized to a low-fat diet (weighted mean difference 3.3 kg, 95% CI −5.3 to
−1.4 kg) (19). Notably, after 12 months this difference dissipated (weighted mean differ-
ence −1.0 kg, 95% CI −3.5 to 1.5 kg; Fig. 2) (19). This metaanalysis also compared the
effect of the two dietary patterns on cardiovascular disease risk factors and found that
after 6 months triglyceride and HDL cholesterol level changes were more favorable in
the low-carbohydrate diet group, but total cholesterol and LDL cholesterol level changes
were more favorable in the low-fat group. Overall, existing trials of low-carbohydrate
diets/high-fat diets have shown greater short-term weight loss (within 6 months) than
low-fat diets; however, most studies have been small and inconclusive. Similar findings
have been shown for low-carbohydrate/high-protein diets (generally 25% energy) (20).
3. MEDITERRANEAN-TYPE DIETS
The Mediterranean dietary pattern emphasizes moderate consumption of fat (~40%
energy) primarily from foods high in monounsaturated fatty acids, such as olive oil and
encourages consumption of fruits, vegetables, tree nuts, legumes, whole grains, and fish
as well as moderate consumption of alcohol (21). A review of trials assessing the effect
of the Mediterranean diet on disease prevention identified three studies that evaluated
change in body weight (22). Of these, only the trial by McManus et al. (23) was able to
provide sound evidence for a beneficial role of the Mediterranean diet on weight loss.
In their trial, individuals were randomized to either a moderate-fat energy-restricted
diet (35% energy from fat) or a low-fat energy-restricted diet (20% energy from fat).
After 18 months, the moderate-fat group had decreases in body weight (4.1 kg), BMI
(1.6 kg/m2), and waist circumference (6.9 cm) while the low-fat group had increases of
2.9 kg, 1.4 kg/m2, and 2.6 cm, respectively (P < 0.001). After extending the study for
140 Hu
an additional year, mean weight loss in the moderate fat group was significantly greater
than that in the low fat group, illustrating the sustainability of a Mediterranean dietary
pattern compared with traditional low-fat recommendations. Though compelling as they
are, these results need to be further substantiated, and it should be noted that the dropout
rate among participants was relatively high. Similarly a study by Esposito et al. (24),
which randomized individuals with the metabolic syndrome to either a prudent diet
(total fat < 30% energy) or Mediterranean diet, found that after 2 years, mean (SD) body
weight loss was higher in patients in the Mediterranean diet group (4.0 [1.1] kg) than
in the low-fat diet group (1.2 [0.6] kg; P < .001). However, it is difficult to differentiate
whether these findings are a consequence of the more intensive weight loss counseling
received by the Mediterranean diet group relative to the low-fat diet group. Of particular
interest was the finding that levels of inflammatory markers were significantly reduced
in individuals on the Mediterranean diet compared with individuals on the low-fat diet.
Such findings have recently been corroborated by Estruch et al. (25) who evaluated
the short-term effects of two ad libitum Mediterranean diets (supplemented with either
1 L/week of free virgin olive oil or 30 g/day of free tree nuts (walnuts, almonds, and
hazelnuts)) versus those of an ad libitum low-fat diet on intermediate markers of cardio-
vascular disease. Compared with participants in the low-fat diet group, after 3 months
those in the two Mediterranean diet groups had decreased systolic and diastolic blood
pressure, blood glucose levels, and inflammatory markers and increased HDL levels.
Despite much higher amounts of dietary fat in the Mediterranean diet groups, supple-
mented with olive oil or nuts, there was no difference in body weight between the inter-
vention and low-fat groups.
One of the most desirable features of the Mediterranean diet relative to traditional
low-fat diets is its ability to improve cardiovascular disease risk factors. However, given
the large number of carbohydrate-rich foods consumed in the Mediterranean diet, such
a dietary pattern should include mostly low-GI carbohydrates. Though not explicitly
studied, it has been suggested that traditional Mediterranean diets may enhance weight
loss by providing a sustainable dietary pattern that offers a variety of healthy, portion-
controlled, palatable foods.
4. INDIVIDUAL FOODS AND BEVERAGES
4.1. Nuts
Substantial evidence from epidemiologic studies and clinical trials indicates that high
nut consumption has beneficial effects on blood lipids and cardiovascular risk (16). A
major concern is that because of their high fat content and high energy density, higher
consumption of nuts may cause weight gain and obesity. However, several cross-sec-
tional analyses of large cohort studies, including the Adventist Health Study (26) and the
NHS (27), have shown that people who consume nuts regularly tend to weigh less than
those who rarely consume them.
A 28-month prospective study conducted in Spain found an association between
higher nut consumption and lower risk of weight gain. Compared with those who never
or almost never ate nuts, participants who ate nuts two or more times per week had a
31% (relative risk, 0.69; 95% CI, 0.53–0.90) lower risk of gaining at least 5 kg during
the follow-up. Overall, participants who frequently consumed nuts gained an average of
Chapter 7 / Diet and Physical Activity in the Prevention of Obesity 141
0.42 kg less than those who rarely consumed nuts (28). In the NHS, nut consumption was
inversely associated with risk of type 2 diabetes after adjustment for age, BMI, family
history of diabetes, physical activity, smoking and alcohol, and total energy intake (29).
The multivariate relative risk of women who consumed nuts at least five times per week
(1 oz. serving size) compared with those who never/almost never ate nuts was 0.73 (95%
CI, 0.60–0.89, P for trend <0.001). Sixteen-year average weight gain was also slightly
lower among those who consumed nuts at least five times per week compared with those
who rarely ate them (6.2 kg vs. 6.5 kg, respectively).
Several trials of nut consumption without constraints on body weight have shown no
significant weight changes in groups assigned higher consumption of nuts (30). Three
months of follow-up in the PREDIMED Study, which was conducted in Spain, found
that Mediterranean diets supplemented with tree nuts improved cardiovascular risk
factors but did not lead to weight gain when compared with a low-fat diet (25). Wien
and colleagues (31) also demonstrated that substitution of almonds (84 g/day) for car-
bohydrates in a formula-based low-calorie diet resulted in greater weight loss during a
24-week intervention among 65 overweight and obese adults.
These epidemiologic and clinical trial data indicate that in free-living subjects,
higher nut consumption does not cause greater weight gain; rather, incorporating nuts
into hypocaloric diets may be beneficial for weight control. The mechanisms for these
observations are unclear but could be related to higher amounts of protein and fiber in
nuts, which may enhance satiety and suppress hunger (32). In dietary practice, the ma-
jority of energy contained in nuts appears to be balanced by reductions in other sources
of energy, especially carbohydrates. This may explain the lack of predicted weight gain
in nut-supplemented diets (33). Increased fecal loss of fat due to incomplete mastication
of nuts leads to loss of available energy; this has also been suggested as an explanation
for the lack of expected weight gain among those who eat nuts (30).
4.2. Whole Grains
Grains are staple foods in most societies. In traditional diets, grain were typically
consumed either in whole intact form or as coarse flours produced from stone grind-
ing. Grinding or milling using modern technology produces fine flours with very small
particle size. Milling also removes most of the bran and much of the germ. The result-
ing refined grain products contain more starch but lose substantial amount of dietary
fiber, vitamins, minerals, essential fatty acids, and phytochemicals. Because of loss of
the outer bran layer and pulverization of the endosperm, refined grains are digested
and absorbed more rapidly than whole grain products and tend to cause more rapid and
larger increases in levels of blood glucose and insulin. Thus, whole grain products such
as whole wheat breads, brown rice, oats, and barley usually have lower glycemic index
(GI) values than refined grains (12). Whole grains are also rich in fiber, antioxidant vita-
mins, magnesium, and phytochemicals.
During 12 years of follow-up in the NHS, Liu and colleagues (34) examined the rela-
tionship between changes in intakes of dietary fiber and whole or refined-grain products
and weight gain. Increased consumption of whole grains was associated with a lower mean
4-year weight gain (1.58 kg in the lowest quintile and 1.07 kg in the highest quintile; P
for trend < 0.0001). In contrast, increased intake of refined grains was related to greater
weight gain (from 0.99 to 1.65 kg; P for trend <0.0001). These findings are consistent
142 Hu
with those in a related study on associations between whole-grain, bran, and cereal-fiber
consumption and weight in a cohort of men from the HPFS (35). During 8 years of
follow-up, increased whole-grain intake was inversely associated with long-term weight
gain (P for trend <0.0001). There was also a dose–response relationship; each 40 g/day
increment in whole-grain intake from all foods reduced weight gain by 0.49 kg. Bran
from fortified-grain foods further reduced the risk of weight gain (P for trend = 0.01) by
0.36 kg for every 20 g/day increase in consumption. Correction for measurement errors
in assessing dietary changes strengthened these associations (each 40 g/day increment
in whole-grain intake from all foods reduced weight gain by 1.1 kg).
4.3. Sugar Sweetened Beverages
Sugar-sweetened beverages have received growing attention as potential contributors
to the obesity and diabetes epidemic because of dramatically increased consumption in
the past several decades. Energy contained in beverages seems less well detected by the
body, and subsequent food intake is poorly adjusted to account for the energy intake
from beverages. Sugar-sweetened beverages have been associated with weight gain in
clinical studies and observational studies among children and adults (36). The high sugar
loads from sugar-sweetened beverages may also have detrimental effects on glucose
metabolism leading to diabetes, beyond their potential contribution to obesity. In the
Nurses’ Health Study II, a higher consumption of sugar-sweetened beverages was asso-
ciated with a greater magnitude of weight gain and an increased risk for development
of type 2 diabetes in women (37) (Fig. 3). After adjustment for potential confounders,
women consuming one or more sugar-sweetened soft drinks per day had an RR of type
80
78
r = 0.022
76
Weight (in Kg)
low-high-high
74
low-high-low
72 high-low-high
r = 0.021 high-low-low
70
68
66
1991 1995 1999
Year
Fig. 3. Mean weight in 1991, 1995, and 1999 according to trends in sugar-sweetened soft drink
consumption in 1,969 women who changed consumption between 1991 and 1995 and either
changed or maintained level of consumption until 1999. Low and high intakes were defined as
£1 per week and ³1 per day. The number of subjects were: low–high–high = 323, low–high–low
= 461, high–low–high = 110, and high–low–low = 746. Groups with similar intake in 1991 and
1995 were combined for estimates for these time points. Means were adjusted for age, alcohol
intake, physical activity, smoking, postmenopausal hormone use, oral contraceptive use, cereal
fiber intake, and total fat intake at each time point. Adapted from (37).
Chapter 7 / Diet and Physical Activity in the Prevention of Obesity 143
2.5
2.0 1.85
Relative Risk
150 139 1.41
1.5
1.00 1.00 1.06 1.11
1.0
0.5
0.0
<1/mo 1-4/mo 2-6/wk >=1/d
Sugar-sweetened soft drink consumption
multivariate adjusted multivariate + BMI
Fig. 4. Multivariate relative risks (RRs) of type 2 diabetes according to sugar-sweetened soft drink
consumption in the Nurses’ Health Study II 1991–1999. Multivariate RRs were adjusted for age, al-
cohol (0, 0.1–4.9, 5.0–9.9, 10+ g/day), physical activity (quintiles), family history of diabetes, smok-
ing (never, past, current), postmenopausal hormone use (never, ever), oral contraceptive use (never,
past, current), intake (quintiles) of cereal fiber, magnesium, trans fat, polyunsaturated:saturated
fat, and consumption of sugar-sweetened soft drinks, diet soft drinks, fruit juice, and fruit punch
(other than the main exposure, depending on model). Adapted from (37).
2 diabetes of 1.83 (95% CI: 1.42–2.36; P < .001 for trend) compared with those who
consumed less than one of these beverages per month. The RR for extreme categories
further controlling for BMI was 1.39 (95% CI: 1.07–1.76; P for trend = 0.012) (Fig. 4).
This finding suggests that BMI accounted for about half of the excess risk.
5. PHYSICAL ACTIVITY
Midlife weight gain is a widespread phenomenon in most populations. Hill and col-
leagues (38) estimated that US adults have been gaining an average of 0.45–0.90 kg/
year in the decades since the epidemic of obesity started. Likewise, Brown and col-
leagues (39) estimated that middle-aged Australian women add an average of 0.5 kg/
year. For most people, midlife weight gain reflects gain in body fat, sometimes accom-
panied by loss of lean body mass with aging. Because weight loss and maintenance are
very difficult for obese individuals, finding ways to prevent age-related weight gain is
of critical importance.
Over the 4-year follow-up period in the Health Professionals’ Follow-up Study (40)
men who increased vigorous exercise (including jogging, running, lap swimming, bicy-
cling and rowing, calisthenics and racquet sports) to 1.5 h/week, decreased TV viewing,
and stopped eating between meals, lost an average of 1.4 kg, compared with a weight
gain of 1.4 kg among the overall population. Those who maintained a relatively high level
of vigorous physical activity over time (at least 1.5 h/week) had the lowest prevalence
of obesity as well as the smallest increase in body weight (Fig. 5). These data suggest
that increasing and maintaining vigorous activity and decreasing TV use are important
to prevent weight gain over 4 years.
Schmitz and colleagues (41) examined the longitudinal relationship between changes
in physical activity and weight gain during 10 years of follow-up among 5,115 black
144 Hu
30
25
Percent Obese
20
15
10
5
0
Maintain Increase Decrease Maintain Low
High Activity Activity Activity Activity
1986 1988 1990 1992
Fig. 5. Prevalence of obesity (BMI 27.8) over time for different patterns of recreational vigorous
physical activity. This figure is based on 3,666 nonsmoking, non-hypertensive, and nonhyperc-
holesterolemic men aged 45–54 years (in 1986). Adapted from (40).
and white men and women aged 18–30 years at baseline in the Coronary Artery Risk
Development in Young Adults (CARDIA) Study. After adjustment for secular trend, age,
clinic site, education, smoking, alcohol intake, parity, percentage of energy intake from
fat, and changes in these variables over time, increasing physical activity was significantly
associated with decreasing weight gain in all four race and sex subgroups. Specifically,
increasing high-intensity activity (requiring 6 MET hours) by 2 h/week offset observed
weight gain for all groups but black men. The benefits of exercise in preventing weight
gain were much greater for obese subjects than for those of normal weight at baseline.
In addition, an increase in physical activity in the 2–3 years of follow-up was associ-
ated with a slowing of weight gain during the subsequent 5-year follow-up; the average
attenuation of 5-year weight gain was approximately 1 kg among those who increased
their activity in the first 2–3 years of follow-up (by 1 h/week of high intensity activ-
ity) relative to those who decreased their activity. These results suggest that increasing
physical activity slows long-term weight gain.
In a subsequent analysis of data from the Nurses’ Health Study (42), we exam-
ined the relationship between walking, sedentary behavior (especially prolonged TV
watching), and risk of obesity and type 2 diabetes among 50,277 healthy nonobese
women at baseline in 1992. During 6 years of follow-up, 3,757 (7.5%), the women
who had a BMI of less than 30 kg/m2 in 1992 became obese (BMI 30 kg/m2). In the
multivariate analyses adjusting for age, smoking, exercise level, dietary factors, and
other covariates, each brisk walk for 1 h/day was associated with a 24% (95% CI,
19–29%) reduction in obesity, and standing or walking around at home (2 h/day) with
a 9% (95% CI, 6–12%) reduction in obesity. In contrast, each 2 h/day increment in
TV watching was associated with a 23% (95% CI, 17–30%) increase in obesity; and
each 2 h/day increment in sitting at work was associated with a 5% (95% CI, 0–10%)
increase in obesity. There was a significant association between brisk walking and re-
duced risk of type 2 diabetes. Conversely, time spent watching TV was associated with
increased diabetes risk. It was estimated that in this cohort, 30% (95% CI, 24–36%)
Chapter 7 / Diet and Physical Activity in the Prevention of Obesity 145
of new cases of obesity and 43% (95% CI, 32–52%) of new cases of diabetes could
be prevented by adopting a relatively active lifestyle (<10 h/week of TV watching
and 30 min/day of brisk walking).
6. SUMMARY
Although diet is widely believed to play a major role in obesity, the impact of specific
dietary factors remains elusive. Cumulative epidemiologic and clinical-trial evidence
indicates that there is no “magic bullet” for weight control. Rather, many individual die-
tary factors each exert a modest effect on body weight, and over time, cumulative effects
of small changes in daily energy balance lead to weight gain and obesity (43). Although
dietary fat has long been considered the main culprit behind obesity, large prospective
cohort studies and long-term randomized clinical trials have not demonstrated a major
role of dietary fat in obesity. In contrast, emerging evidence suggests potential weight
control benefits by lowering refined carbohydrates and glycemic loads, but prospective
data are limited. Increasing consumption of protein is also thought to be of potential
benefit; however, long-term data on protein and body weight are lacking.
Currently, there is no conclusive evidence that one popular diet is superior to another
in long-term weight control. Clearly, one diet does not fit all. Thus, when prescribing
such diets to patients, it is important to consider cultural habits and food preference to
maximize long-term adherence (11). For most patients, rapid weight loss should not be
the goal for dietary therapy. Instead, dietary recommendations should target gradual
and sustained weight loss and long-term benefits on cardiovascular health. Toward this
end, one should choose healthy sources of fats and whole grain products, which are
known to be cardio-protective and may also enhance weight loss. Substitution of healthy
sources of protein for refined carbohydrates and added sugar can be also beneficial for
body weight and cardiovascular risk factors. Such macronutrient choices underpin the
role of Mediterranean-style diets in improving cardiovascular disease risk and reducing
major chronic diseases.
Compelling evidence supports that sedentary lifestyle indicated by prolonged TV
watching is an important risk factor for obesity and type 2 diabetes, whereas increasing
physical activity is associated with weight maintenance and a lower risk of obesity and
type 2 diabetes. There are at least two explanations for the observed positive association
between TV watching and diabetes risk. First, TV watching is directly related to obesity
and weight gain, probably due to lower energy expenditure (i.e. less physical activity)
and higher caloric intake. Second, participants who spent more time watching TV tended
to eat more red meat, processed meat, snacks, refined grains, and sweets and less veg-
etables, fruits, and whole grains. Such an eating pattern, which is linked to commercial
advertisements and food cues appearing on TV, may adversely affect diabetes risk.
Most of adults in the US do not engage in regular exercise and substantial propor-
tion of the population is completely sedentary. Also, past several decades have seen an
increasing trend of sedentary behaviors, especially prolong TV watching. The combina-
tion of lack of exercise and increasing sedentary behavior at least partially contributes
to the increasing epidemic of obesity and type 2 diabetes in the US and worldwide.
Public health campaign is urgently needed not only to promote increasing physical
activity but also to reduce sedentary behaviors especially prolonged TV watching in
both adults and children.
146 Hu
Given the obesogenic environment in which we live, characterized by the abundance
of energy dense, processed, and highly convenient foods and sedentary lifestyle, we
should realize that without changing our nutrition and physical activity environment,
for most people, the effects of any kind of weight loss or maintenance diets are difficult
to sustain (11).
REFERENCES
1. Ogden C.L., Carroll M.D., Curtin L.R., et al. Prevalence of overweight and obesity in the United States,
1999–2004. JAMA 2006;295:1549–55.
2. Allison D.B., Fontaine K.R., Manson J.E., et al. Annual deaths attributable to obesity in the United
States. JAMA 1999;282:1530–8.
3. Willett W.C. Dietary fat plays a major role in obesity: no. Obes Rev 2002;3:59–68.
4. Astrup A. Dietary composition, substrate balances and body fat in subjects with a predisposition to
obesity. Int J Obes Relat Metab Disord 1993;17 Suppl 3:S32–6; discussion S41–2.
5. Flatt J.P., Ravussin E., Acheson K.J., et al. Effects of dietary fat on postprandial substrate oxidation
and on carbohydrate and fat balances. J Clin Invest 1985;76:1019–24.
6. Lissner L., Heitmann B.L. Dietary fat and obesity: evidence from epidemiology. Eur J Clin Nutr
1995;49:79–90.
7. Seidell J.C. Dietary fat and obesity: an epidemiologic perspective. Am J Clin Nutr 1998;67(3
Suppl):546S–50S.
8. Heitmann B.L., Lissner L., Sorensen T.I., et al. Dietary fat intake and weight gain in women genetically
predisposed for obesity. Am J Clin Nutr 1995;61:1213–7.
9. Field A.E., Willett W.C., Lissner L., et al. Dietary fat and weight gain among women in the Nurses’
Health Study. Obesity (Silver Spring) 2007;15(4):967–76.
10. Koh-Banerjee P., Chu N.F., Spiegelman D., et al. Prospective study of the association of changes in
dietary intake, physical activity, alcohol consumption, and smoking with 9-y gain in waist circumfer-
ence among 16 587 US men. Am J Clin Nutr 2003;78:719–27.
11. Malik V.S., Hu F.B. Popular weight-loss diets: from evidence to practice. Nat Clin Pract Cardiovasc Med
2007;4:34–41.
12. Bray G.A., Popkin B.M. Dietary fat intake does affect obesity! Am J Clin Nutr 1998;68:1157–73.
13. Howard B.V., Manson J.E., Stefanick M.L., et al. Low-fat dietary pattern and weight change over 7
years: the Women’s Health Initiative Dietary Modification Trial. JAMA 2006;295:39–49.
14. Agriculture UDo. Dietary Guidelines for Americans. 3rd ed. Washington, DC: US Departments of
Agriculture and Health and Human Services; 1990. Home and Garden Bulletin No. 232.
15. Jenkins D.J., Wolever T.M., Taylor R.H., et al. Glycemic index of foods: a physiological basis for
carbohydrate exchange. Am J Clin Nutr 1981;34:362–6.
16. Hu F.B., Willett W.C. Optimal diets for prevention of coronary heart disease. JAMA 2002;288:2569–
78.
17. Chiasson J.L., Josse R.G., Gomis R., et al. Acarbose for prevention of type 2 diabetes mellitus: the
STOP-NIDDM randomised trial. Lancet 2002;359:2072–7.
18. Koh-Banerjee P., Rimm E.B. Whole grain consumption and weight gain: a review of the epide-
miological evidence, potential mechanisms and opportunities for future research. Proc Nutr Soc
2003;62:25–9.
19. Nordmann A.J., Nordmann A., Briel M., et al. Effects of low-carbohydrate vs low-fat diets on weight
loss and cardiovascular risk factors: a meta-analysis of randomized controlled trials. Arch Intern Med
2006;166:285–93.
20. Hu F.B. Protein, body weight, and cardiovascular health. Am J Clin Nutr 2005;82:242S–7S.
21. Willett W.C., Sacks F., Trichopoulou A., et al. Mediterranean diet pyramid: a cultural model for healthy
eating. Am J Clin Nutr 1995;61:1402S–6S.
22. Serra-Majem L., Roman B., Estruch R. Scientific evidence of interventions using the Mediterranean
diet: a systematic review. Nutr Rev 2006;64:S27–47.
Chapter 7 / Diet and Physical Activity in the Prevention of Obesity 147
23. McManus K., Antinoro L., Sacks F. A randomized controlled trial of a moderate-fat, low-energy diet
compared with a low fat, low-energy diet for weight loss in overweight adults. Int J Obes Relat Metab
Disord 2001;25:1503–11.
24. Esposito K., Marfella R., Ciotola M., et al. Effect of a mediterranean-style diet on endothelial dys-
function and markers of vascular inflammation in the metabolic syndrome: a randomized trial. JAMA
2004;292:1440–6.
25. Estruch R., Martinez-Gonzalez MA, Corella D, et al. Effects of a Mediterranean-style diet on cardio-
vascular risk factors: a randomized trial. Ann Intern Med 2006;145:1–11.
26. Fraser G.E., Sabate J., Beeson W.L., et al. A possible protective effect of nut consumption on risk of
coronary heart disease. The Adventist Health Study. Arch Intern Med 1992;152:1416–24.
27. Hu F.B., Stampfer M.J., Manson J.E., et al. Frequent nut consumption and risk of coronary heart disease
in women: prospective cohort study. BMJ 1998;317:1341–5.
28. Bes Rastrollo M., Sabate J., Gomez-Garcia E., et al. Nut consumption and weight gain in a Mediter-
ranean cohort: The SUN Study. Obesity (Silver Spring) 2007;15(1):107–16.
29. Jiang R., Manson J.E., Stampfer M.J., et al. Nut and peanut butter consumption and risk of type 2
diabetes in women. JAMA 2002;288:2554–60.
30. Sabate J. Nut consumption and body weight. Am J Clin Nutr 2003;78(3 Suppl):647S–50S.
31. Wien M.A., Sabate J.M., Ikle D.N., et al. Almonds vs complex carbohydrates in a weight reduction
program. Int J Obes Relat Metab Disord 2003;27:1365–72.
32. Alper C.M., Mattes R.D. Effects of chronic peanut consumption on energy balance and hedonics. Int
J Obes Relat Metab Disord 2002;26:1129–37.
33. Fraser G.E., Bennett H.W., Jaceldo K.B., et al. Effect on body weight of a free 76 Kilojoule (320 calorie)
daily supplement of almonds for six months. J Am Coll Nutr 2002;21:275–83.
34. Liu S., Willett W.C., Manson J.E., et al. Relation between changes in intakes of dietary fiber and grain
products and changes in weight and development of obesity among middle-aged women. Am J Clin
Nutr 2003;78:920–7.
35. Koh-Banerjee P., Franz M., Sampson L., et al. Changes in whole-grain, bran, and cereal fiber consump-
tion in relation to 8-y weight gain among men. Am J Clin Nutr 2004;80:1237–45.
36. Malik V.S., Schulze M.B., Hu F.B. Intake of sugar-sweetened beverages and weight gain: a systematic
review. Am J Clin Nutr 2006;84:274–88.
37. Schulze M.B., Manson J.E., Ludwig D.S., et al. Sugar-sweetened beverages, weight gain, and incidence
of type 2 diabetes in young and middle-aged women. JAMA 2004;292:927–34.
38. Hill J.O., Wyatt H.R., Reed G.W., et al. Obesity and the environment: where do we go from here. Science
2003;299:853–5.
39. Brown W.J., Williams L., Ford J.H., et al. Identifying the energy gap: magnitude and determinants of
5-year weight gain in midage women. Obes Res 2005;13:1431–41.
40. Coakley E.H., Rimm E.B., Colditz G., et al. Predictors of weight change in men: results from the Health
Professionals Follow-up Study. Int J Obes Relat Metab Disord 1998;22:89–96.
41. Schmitz K.H., Jacobs D.R., Jr., Leon A.S., et al. Physical activity and body weight: associations over
ten years in the CARDIA study. Coronary Artery Risk Development in Young Adults. Int J Obes Relat
Metab Disord 2000;24:1475–87.
42. Hu F.B., Li T.Y., Colditz G.A., et al. Television watching and other sedentary behaviors in relation to
risk of obesity and type 2 diabetes mellitus in women. JAMA 2003;289:1785–91.
43. Hu F.B. Chapter 14. Diet, Nutrition, and Obesity. In Obesity Epidemiology, edited by Hu FB. Oxford
University Press. New York 2008;275–300.
8 Diet and Exercise in the Prevention
and Management of the Metabolic
Syndrome
Mary Yannakoulia, Evaggelia Fappa,
Janice Jin Hwang, and Christos S. Mantzoros
KEY POINTS
• The metabolic syndrome (MetSyn) encompasses a constellation of metabolic abnormalities
that are thought to place patients at higher risk for cardiovascular morbidity.
• Many definitions have been proposed, and although the exact mechanisms underlying the
syndrome remain unclear, increased abdominal fat correlated with dyslipidemia, insulin
resistance, and hyperinsulinemia are believed to be the core of its pathophysiology.
• Its increasing prevalence urged the need for preventing and managing strategies. Prevention
of the syndrome includes keeping body weight within the normal range, exercise training,
and consumption of a moderate carbohydrate diet, with moderate consumption of mono or
polyunsaturated fatty acids (omega-3 polyunsaturated fatty acids).
• Current guidelines for the clinical management propose lifestyle changes (diet and physical
activity) as a first-line intervention. However, research in this area is limited.
• Weight loss has been recognized as an important issue in the management of MetSyn, in
addition to exercise training and diet quality.
• Short-term success of lifestyle intervention programs has been observed, though they failed
to sustain long-term effectiveness.
• Multiple follow-up booster sessions proved more effective in maintaining lifestyle changes
than one counseling session at the end of follow-up.
• In conclusion, diet and physical activity have a pivotal role in the prevention and management
of the MetSyn. Hence, it is of major importance to explore strategies to improve adherence
and ensure that patients achieve and maintain lifestyle changes.
Key Words: Metabolic syndrome, Weight loss, Lifestyle intervention, Diet, Physical
activity, Adherence, Behavior modification
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_8,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
149
150 Yannakoulia et al.
1. INTRODUCTION
The metabolic syndrome (MetSyn), also known as syndrome X or insulin resistance
syndrome, constitutes a constellation of symptoms, including obesity, insulin resistance/
glucose intolerance, dyslipidemia, and hypertension, and it is associated with a two to
fourfold increase in cardiovascular morbidity and stroke (1). The increasing prevalence
of MetSyn is concurrent with the alarming increase in the prevalence of obesity and type
2 diabetes. On the basis of the US population data from 1988 to 1994, the prevalence
increased from 6.7% among participants aged 20 through 29 years to 43.5 and 42.0% for
participants aged 60 through 69 years and aged at least 70 years respectively, reaching
an overall percentage of 24.5% (2). Although there has been a controversy surrounding
the exact definition of the syndrome, there is incontrovertible evidence that the risk
factors associated with the MetSyn should and need to be addressed in concert. In this
chapter, the risk factors will be summarized and the literature examining prevention and
clinical management of the syndrome will be discussed.
2. DEFINITION AND PATHOPHYSIOLOGY
OF THE METABOLIC SYNDROME
Although several criteria exist, most criteria include metabolic risk factors, such as
abdominal/central obesity, hypertriglyceridemia, low levels of high density lipoprotein
(HDL) cholesterol, hypertension, and elevated fasting glucose levels. Gerald Reaven
first described “syndrome X” in 1988 proposing insulin resistance to be the critical fac-
tor of the syndrome, predisposing patients to hypertension, hyperlipidemia, and type 2
diabetes mellitus (3). Ten years later the World Health Organization published the first
criteria for the syndrome (4). Since then, a number of definitions have been proposed
(5–7). They could be categorized in two groups depending on the leading cause of the
syndrome, being either visceral obesity or insulin resistance. The different definitions
may lead to research and clinical problems, such as difficulties in comparability between
studies or misclassification of patients.
The pathophysiology of the MetSyn is complex and remains, in most part, unknown.
A full review of the current literature is beyond the scope of this chapter (8) Briefly,
increased abdominal fat correlates with dyslipidemia (9–13), insulin resistance, and
hyperinsulinemia (14) via mechanisms involving increased free fatty acids (15,16) and/or
changes in levels of adipokines, such as adiponectin (17–21), resistin (22–24), and leptin
(25–28). These factors, along with the proinflammatory state associated with obesity
(29,30), may create an unfavorable proatherogenic milieu (31).
Park and colleagues identified risk factors associated with the MetSyn, including
older age, postmenopausal status, Mexican American ethnicity, higher body mass
index, current smoking, low household income, high carbohydrate intake, no alcohol
consumption, and physical inactivity (32). Few randomized control trials specifically
examining incidence or resolution of MetSyn have been conducted so far (33–44);
however, there is overwhelming evidence showing that management of the individual
components of the syndrome can delay or prevent the onset of diabetes, hypertension,
and cardiovascular disease.
Chapter 8 / Diet and Exercise in the Prevention and Management of the Metabolic Syndrome 151
3. PREVENTION OF RISK FACTORS FOR METABOLIC
SYNDROME: THE ROLE OF PHYSICAL FITNESS/ACTIVITY
AND OF DIETARY FACTORS
A cornerstone of prevention lies in avoiding excess body weight (45). Excess body
weight increases the risk for diabetes (46–49), hypertension (50,51), and cardiovascular
disease (49,52). An in-depth examination of the current treatment options for obesity can
be found in Chaps. 15 and 16. In addition to decreasing the risk of adverse metabolic sequel,
weight loss is also associated with decreased levels of inflammatory markers (53–57).
3.1. Physical Fitness and Physical Activity
Several observational studies revealed associations between physical fitness and
likelihood of death from cardiovascular disease. Blair et al. examined 10,224 men and
3,120 women for an average of 8 years follow-up and found that the rate of mortality was
64/10,000 person-years in the least fit men, compared with 18.6/10,000 person-years in
the most fit men (58). Corresponding values for women were 39.5/10,000 person-years
to 8.5/10,000 person-years. These trends remained significant after adjustment for age,
smoking habits, cholesterol levels, systolic blood pressure, fasting blood glucose levels,
parental history of coronary heart disease, and follow-up interval. The same scientific
group has subsequently published several similar prospective studies showing that low
fitness was an independent predictor of mortality in all body mass index groups after
adjustment for other mortality predictors (59).
Another prospective cohort study followed 936 women who required coronary
angiography for a median of 3.9 years (60). Self reported higher physical fitness scores
were found to be associated with fewer coronary artery disease (CAD) risk factors,
less angiographic CAD, and lower risk for adverse cardiovascular events. Furthermore,
asymptomatic men with low cardiorespiratory fitness levels have been shown to be more
likely to develop MetSyn (61).
Most studies to date suggest that exercise confers additional health benefits beyond
those achieved from weight loss or changes in body fat ratios. Chronic exercise is
associated with improvements in triglycerides (62,63), and even a single bout of exercise
has been shown to induce favorable changes in lipid metabolism of healthy men (64).
Physical training reduces skeletal muscle lipid levels and insulin resistance regardless
of body mass index (65,66). In addition, exercise may also exert favorable effects on
adipokines, such as adiponectin and other inflammatory markers, without significant
changes in body weight (67,68).
3.2. Dietary Factors
Several dietary parameters have been related to MetSyn risk factors. Regarding lipid
metabolism, trans-fatty acids are associated with increased low density lipoprotein
(LDL) and decreased HDL cholesterol levels (69), whereas omega-3 fatty acids, in the
form of fish oils, were effective in lowering triglyceride levels (and blood pressure) in
people with mild hypertension (70). Even though there has been a controversy among
studies regarding the effect of polyunsaturated fatty acids consumption on glycemic con-
trol (71,72), substituting saturated for unsaturated fatty acids increases insulin sensitivity
in healthy men and women (73). Additionally, it has been shown that trans-fatty acids
152 Yannakoulia et al.
increased risk of diabetes (74). However, restricting saturated fatty acids and replacing
with carbohydrates leads to lower HDL levels as well, so as to keep fat consumption
relatively high and at the same time avoiding adverse effects on health, substituting satu-
rated with mono or polyunsaturated fat seems to provide the optimal result (75).
On the topic of carbohydrates, it seems that glycemic and insulinemic responses
to ingestion of carbohydrates depend on the glycemic index or load (76). More
precisely, subjects in the highest quintile of glycemic load diet compared with low-
est quintile subjects had higher triglyceride and lower HDL cholesterol levels (77,78).
High glycemic index foods increase the demand for insulin, creating additional stress
on beta-cell function and impairing glucose tolerance (79). Alternatively, low/moderate
carbohydrate diets (from 60 g of carbohydrates/day to 40% of energy from carbohydrates)
were associated with improvements in HDL cholesterol and triglycerides compared
with high carbohydrate or low fat diets; however, changes in LDL cholesterol were
not in favor of low as opposed to moderate carbohydrate diets (80,81). A decrease in
glycemic load with the use of acarbose, an alpha-glucosidase inhibitor that slows the
digestion and absorption of starch, led to a significant decrease in blood pressure and an
increased reversion of impaired to normal glucose tolerance (82,83).
Regarding alcohol consumption, 30 g/day of alcohol intake reduced fasting insulin
concentration and triglyceride concentration, and increased insulin sensitivity compared
with no consumption (84). A prospective cohort from the Quebec Cardiovascular Study
followed 1,966 cardiovascular heart disease free men for 13 years and found that men who
consumed ³15.2 g of alcohol/day had elevated plasma HDL cholesterol concentrations
(P < 0.001), and lower plasma concentrations of insulin (P = 0.01), C-reactive protein
(P = 0.01), and fibrinogen (P < 0.001) than men who consumed <1.3 g of alcohol/day
(85). On the contrary, high (greater than 3 drinks/day) alcohol consumption is associated
with hypertension, but this association has not been consistently shown with moderate
amounts of intake (86).
Beyond individual nutrients or foods, holistic approaches targeting overall lifestyle
changes provide interesting results. The Diabetes Prevention Program randomized trial
compared the effects of placebo, metformin, and intensive lifestyle intervention (including
moderate intensity physical activity such as brisk walking for at least 150 min/week) on
prevention of the MetSyn in 3,234 subjects with impaired glucose tolerance. After 3 years,
the cumulative incidence of MetSyn was 51, 45, and 34% in the placebo, metformin, and
lifestyle groups, respectively (87). Incidence of the MetSyn was reduced by 41% in the
lifestyle group and by 17% in the metformin group, compared with placebo. Interestingly,
the effects of lifestyle intervention on MetSyn prevention appeared to be more strongly
related to decreased waist circumference and improvements in blood pressure as opposed
to dyslipidemia. The Finnish Diabetes Prevention Study, similarly, found that intensive
lifestyle intervention resulted in improved glucose levels, lipid markers, and body mass
index after 3 years compared with controls (88).
4. CLINICAL MANAGEMENT OF METABOLIC SYNDROME
The high prevalence of the MetSyn and its ability to detect people at risk for cardio-
vascular disease or type II diabetes mellitus led the National Cholesterol Education Pro-
gram to publish, in 2001, clinical management guidelines. Recommendations include
Chapter 8 / Diet and Exercise in the Prevention and Management of the Metabolic Syndrome 153
weight reduction and increase in physical activity as first-line intervention beyond this,
specific treatments are proposed against the lipid and the nonlipid components of the
MetSyn (6). Long-term lifestyle changes constitute, therefore, the cornerstone for the
management of MetSyn.
4.1. Weight Loss and Energy Deficit
A few studies have evaluated the efficacy of lifestyle modification in resolving the
syndrome. In the majority of them, weight reduction was the main goal and, most likely,
the underlying mechanism leading to improvement in MetSyn parameters. Weight loss
was found to favorably affect all the individual components (51,89,90): it is associated
with a significant improvement in glucose control and lipid and nonlipid abnormalities
(33,34). Ten percent weight loss, compared with lower rates, has been documented to
result in greater reductions in the MetSyn components, with patients going beyond the
10% reduction experiencing greater short and long-term (16 months) benefits (35).
Interestingly, benefits from weight loss may be present even at high posttreatment body
mass index levels (³30 kg/m2) (36,91).
Caloric restriction along with a low-fat or a high omega-3/low saturated fatty acids diet
were found to have a beneficial effect on the MetSyn (37–39). A hypocaloric, prudent
dietary pattern, rich in fruits and vegetables, consumed for a period of 24 weeks, has
also been successfully applied for the management of MetSyn (40). Furthermore, great
energy deficits, achieved by very low calorie diets, with or without exercise, resulted in
favorable changes to the components of the MetSyn (36,41), as did the supplementary
use of orlistat, a pancreatic lipase inhibitor, for achieving energy restriction (42).
4.2. Diet Quality
Research is limited with regard to the effect of dietary manipulation of macronutrient
content in patients with MetSyn. Although some evidence support the view that the
modest weight loss, rather than the macronutrient composition per se, induces changes
in MetSyn parameters (44), there are studies that have found improvements in blood
lipid profile and pressure by modifying macronutrient composition of the diet but not
energy balance and keeping stable body weight (92,93).
Although people on a low-fat, high-carbohydrate diet have greater odds of having MetSyn,
compared with those on a low-carbohydrate, high-fat diet (94), this is in disagreement with
data from patients having the MetSyn. When a high-carbohydrate, low-fat diet was compared
with a high-fat and protein, low carbohydrate diet, all the components of MetSyn decreased
significantly with both diets (except of HDL cholesterol, which remained unchanged) (95).
On the basis of the fact that low-carbohydrate diet was associated with a greater decrease
in the prevalence of hypertension and hypertriacylglycerolemia, it has been proposed that
tailoring dietary interventions to the specific presentation of the MetSyn may be the best
way of reducing the risk factors for cardiovascular disease (95).
Apart from the effect of individual macronutrients, dietary patterns have also been
examined in relation to MetSyn parameters. In one study, consumption of a Mediterranean-
style diet was shown to improve endothelial function and significantly reduce markers of
systemic vascular inflammation in MetSyn patients, even with modest weight loss (43).
Participants in the Mediterranean diet intervention showed a reduction in the components
of the syndrome to that extent that the overall prevalence of MetSyn was reduced by
154 Yannakoulia et al.
approximately one half. The authors commented that, as the analysis was adjusted for
changes in body weight, the overall reduction in the prevalence of the metabolic syndrome
probably represents a conservative measure. Adoption of a Mediterranean-style diet rich
in whole grains, fruits, vegetables, legumes, walnuts, and olive oil is a safe and effective
strategy in reducing both the prevalence of MetSyn and its associated cardiovascular risk.
Furthermore, another dietary pattern, the DASH diet (Dietary Approach to Stop Hyperten-
sion), has been shown to favorably influence MetSyn parameters, and particularly blood
pressure. Adoption of a DASH diet, in the context of an intensive behavioral intervention
including the established lifestyle modifications for lowering blood pressure, may be a
key feature to achieve a decline in blood pressure in MetSyn patients (96).
4.3. Physical Activity
The beneficial effects of physical activity on MetSyn are well established: increases
in physical activity improve individual metabolic parameters or combinations of them
(33,37,97), either directly or by promoting weight reduction. MetSyn resolved in 30% of
patients after 20 weeks of supervised aerobic exercise training (98). In addition, 8 weeks
of low-intensity endurance exercise induced a moderate decrease in insulin resistance (99).
As weight loss constitutes an important therapeutic goal for the treatment of MetSyn,
increase and maintenance of physical activity levels further contributes to this goal by
supporting weight loss maintenance (100).
The type of physical activity varies greatly among studies, from nonprescribed
ad libitum physical activity (35,36,43) to supervised exercise, specified in terms of
duration and type (33,34,37–40). Resistance and aerobic exercise have been proven to
be equally effective in improving metabolic parameters (101). Concerning, the intensity
and amount of aerobic exercise, a modest amount of moderate-intensity exercise, in the
absence of dietary changes, significantly improved MetSyn and, thus, supported the
recommendation that adults should get 30 min of moderate-intensity exercise every day
(102). Furthermore, there was an indication that moderate-intensity may be better than
vigorous-intensity exercise for improving MetSyn.
Changes in physical activity were among the principal goals of most lifestyle interven-
tions for MetSyn, in addition to dietary modifications (33–40,43). In one study, adding an
exercise component to a dietary intervention led to a significant reduction only in systolic
blood pressure compared with the nonexercise, diet-only group (33). Alternatively, add-
ing a dietary modification component to an exercise intervention had beneficial effects
on several parameters, namely weight reduction, fasting glucose levels, and diastolic
blood pressure (37). Furthermore, combining diet and exercise had additive effects on the
resolution of MetSyn compared with either treatment alone (103). It should be pointed
out, however, that, in those interventions that include both exercise changes and dietary
modifications, improvements in MetSyn components were not specifically attributed to
the exercise or the dietary component (33–40,43), and we cannot draw conclusions on
the relative significance of these two lifestyle parameters.
The effect of physical activity has also been examined in relation to the maintenance
of changes. To further improve MetSyn parameters or maintain achieved changes, the
addition of exercise at the end of a weight-reduction program has been found to be as
effective as dietary therapy alone; in other words, physical activity did not confer further
benefit to the parameters studied (91). The authors postulated that either the exercise dose
Chapter 8 / Diet and Exercise in the Prevention and Management of the Metabolic Syndrome 155
was too small or the adherence to the exercise sessions was not at the prescribed levels.
Nevertheless, there is accumulating evidence in support to that long-term maintenance
of weight loss is facilitated by regular physical activity (104–106). This is of great value
considering that body weight is an important factor affecting MetSyn parameters.
4.4. Adherence to the Therapeutic Intervention
Adoption of a healthy balanced diet requires behavioral changes in relation to meal
planning, food selection, food preparation, portion control, and appropriate responses to
eating challenges. Long-term adherence is required and its importance has been extensively
discussed in the context of obesity or diabetes (107–109). However, evidence regarding
MetSyn is limited. Greater adherence has been correlated with greater decreases in Met-
Syn parameters (40). Anderssen et al. (39) reported significant improvements in MetSyn
components in the group of “good responders,” i.e. those belonging to the highest tertile
of change for body weight and oxygen uptake. This finding could be translated as “best
adherence, best results.”
With regard to maintenance, although significant changes in MetSyn parameters
have been observed in the short-term (34,37,40,109), in the absence of posttreatment
booster sessions, subjects tend to maintain only part of the changes achieved or, for
some components, they even return to their initial status (38). On the contrary, when
active follow-up was included in the treatment (as three to four follow-up visits per year
for 20 months), a further improvement in MetSyn components was achieved (35).
As noted earlier, low adherence to prescribed exercise sessions was suggested
to mediate the modest changes observed in the components of the MetSyn (91). In a
study by Singh et al. (40), control and intervention groups were given written advice to
increase physical activity, whereas the intervention group also participated in a super-
vised exercise program. Improvement in the MetSyn components was achieved only in
the intervention group, consistent with the finding that this group experienced a greater
increase in physical activity, i.e., greater compliance to the program. Therefore, most
investigators preferably use supervised exercise treatment (33,34,37–39), instead of an
ad libitum exercise component (35,36,43).
5. CONCLUSION
There is a growing body of literature supporting the important role of diet and physical
activity in the prevention and management of the MetSyn. To date, most of the lifestyle
interventions had a favorable effect on the MetSyn; dietary changes constitute the core
of the treatment, weight reduction plays a key role, and exercise confers an additional
favorable effect. Nonetheless, it is of major importance to explore strategies to improve
adherence and ensure that patients achieve and maintain lifestyle changes.
REFERENCES
1. Levantesi G, Macchia A, Marfisi R, et al. Metabolic syndrome and risk of cardiovascular events after
myocardial infarction. J Am Coll Cardiol 2005;46:277–83.
2. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from
the third National Health and Nutrition Examination Survey. JAMA 2002;287:356–9.
156 Yannakoulia et al.
3. Reaven GM. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes 1988;37:
1595–607.
4. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complica-
tions. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation.
Diabet Med 1998;15:539–53.
5. Balkau B, Charles MA. Comment on the provisional report from the WHO consultation. European
Group for the Study of Insulin Resistance (EGIR). Diabet Med 1999;16:442–3.
6. Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert
Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment
Panel III). Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults.
JAMA 2001;285:2486–97.
7. Bloomgarden ZT. American Association of Clinical Endocrinologists (AACE) consensus
conference on the insulin resistance syndrome: 25–26 August 2002, Washington, DC. Diabetes Care
2003;26:1297–303.
8. Moller DE, Kaufman KD. Metabolic syndrome: a clinical and molecular perspective. Annu Rev Med
2005;56:45–62.
9. Avramoglu RK, Basciano H, Adeli K. Lipid and lipoprotein dysregulation in insulin resistant states.
Clin Chim Acta 2006;368:1–19.
10. Balasubramanyam A, Sekhar RV, Jahoor F, Jones PH, Pownall HJ. Pathophysiology of dyslipidemia
and increased cardiovascular risk in HIV lipodystrophy: a model of ‘systemic steatosis’. Curr Opin
Lipidol 2004;15:59–67.
11. Grundy SM. Atherogenic dyslipidemia associated with metabolic syndrome and insulin resistance.
Clin Cornerstone 2006;8 Suppl 1:S21–7.
12. Lewis GF, Carpentier A, Adeli K, Giacca A. Disordered fat storage and mobilization in the pathogenesis
of insulin resistance and type 2 diabetes. Endocr Rev 2002;23:201–29.
13. Schondorf T, Maiworm A, Emmison N, Forst T, Pfutzner A. Biological background and role of
adiponectin as marker for insulin resistance and cardiovascular risk. Clin Lab 2005;51:489–94.
14. Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection,
Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report.
National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment
of High Blood Cholesterol in Adults (Adult Treatment Panel III). Circulation 2002;106:3143–421.
15. Boden G. Role of fatty acids in the pathogenesis of insulin resistance and NIDDM. Diabetes 1997;46:3–10.
16. Boden G , Shulman GI. Free fatty acids in obesity and type 2 diabetes: defining their role in the
development of insulin resistance and beta-cell dysfunction. Eur J Clin Invest 2002;32 Suppl 3:14–23.
17. Berg AH, Combs TP, Du X, Brownlee M, Scherer PE. The adipocyte-secreted protein Acrp30 enhances
hepatic insulin action. Nat Med 2001;7:947–53.
18. Berg AH, Combs TP, Scherer PE. ACRP30/adiponectin: an adipokine regulating glucose and lipid
metabolism. Trends Endocrinol Metab 2002;13:84–9.
19. Combs TP, Berg AH, Obici S, Scherer PE, Rossetti L. Endogenous glucose production is inhibited by
the adipose-derived protein Acrp30. J Clin Invest 2001;108:1875–81.
20. Yamauchi T, Hara K, Kubota N, et al. Dual roles of adiponectin/Acrp30 in vivo as an anti-diabetic and
anti-atherogenic adipokine. Curr Drug Targets Immune Endocr Metabol Disord 2003;3:243–54.
21. Yamauchi T, Kamon J, Ito Y, et al. Cloning of adiponectin receptors that mediate antidiabetic metabolic
effects. Nature 2003;423:762–9.
22. Banerjee RR, Rangwala SM, Shapiro JS, et al. Regulation of fasted blood glucose by resistin. Science
2004;303:1195–8.
23. Rajala MW, Qi Y, Patel HR, et al. Regulation of resistin expression and circulating levels in obesity,
diabetes, and fasting. Diabetes 2004;53:1671–9.
24. Steppan CM, Bailey ST, Bhat S, et al. The hormone resistin links obesity to diabetes. Nature
2001;409:307–12.
25. Chu NF, Chang JB, Shieh SM. Plasma leptin, fatty acids, and tumor necrosis factor-receptor and insulin
resistance in children. Obes Res 2003;11:532–40.
26. Lee JH, Chan JL, Sourlas E, Raptopoulos V, Mantzoros CS. Recombinant methionyl human leptin
therapy in replacement doses improves insulin resistance and metabolic profile in patients with lipoatrophy
Chapter 8 / Diet and Exercise in the Prevention and Management of the Metabolic Syndrome 157
and metabolic syndrome induced by the highly active antiretroviral therapy. J Clin Endocrinol Metab
2006;91:2605–11.
27. Lichnovska R, Gwozdziewiczova S, Chlup R, Hrebicek J. Serum leptin in the development of insulin
resistance and other disorders in the metabolic syndrome. Biomed Pap Med Fac Univ Palacky Olomouc
Czech Repub 2005;149:119–26.
28. Zimmet P, Boyko EJ, Collier GR, de Courten M. Etiology of the metabolic syndrome: potential role
of insulin resistance, leptin resistance, and other players. Ann N Y Acad Sci 1999;892:25–44.
29. Hotamisligil GS, Shargill NS, Spiegelman BM. Adipose expression of tumor necrosis factor-alpha:
direct role in obesity-linked insulin resistance. Science 1993;259:87–91.
30. Spiegelman BM, Hotamisligil GS. Through thick and thin: wasting, obesity, and TNF alpha. Cell
1993;73:625–7.
31. Moller DE, Chang PY, Yaspelkis BB, III, Flier JS, Wallberg-Henriksson H, Ivy JL. Transgenic mice
with muscle-specific insulin resistance develop increased adiposity, impaired glucose tolerance, and
dyslipidemia. Endocrinology 1996;137:2397–405.
32. Park YW, Zhu S, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB. The metabolic syndrome:
prevalence and associated risk factor findings in the US population from the Third National Health and
Nutrition Examination Survey, 1988–1994. Arch Intern Med 2003;163:427–36.
33. Christ M, Iannello C, Iannello PG, Grimm W. Effects of a weight reduction program with and without
aerobic exercise in the metabolic syndrome. Int J Cardiol 2004;97:115–22.
34. Villareal DT, Miller BV, III, Banks M, Fontana L, Sinacore DR, Klein S. Effect of lifestyle in-
tervention on metabolic coronary heart disease risk factors in obese older adults. Am J Clin Nutr
2006;84:1317–23.
35. Muzio F, Mondazzi L, Sommariva D, Branchi A. Long-term effects of low-calorie diet on the metabolic
syndrome in obese nondiabetic patients. Diabetes Care 2005;28:1485–6.
36. Case CC, Jones PH, Nelson K, O’Brian Smith E, Ballantyne CM. Impact of weight loss on the metabolic
syndrome. Diabetes Obes Metab 2002;4:407–14.
37. Watkins LL, Sherwood A, Feinglos M, et al. Effects of exercise and weight loss on cardiac risk factors
associated with syndrome X. Arch Intern Med 2003;163:1889–95.
38. Lindahl B, Nilsson TK, Asplund K, Hallmans G. Intense nonpharmacological intervention in subjects
with multiple cardiovascular risk factors: decreased fasting insulin levels but only a minor effect on
plasma plasminogen activator inhibitor activity. Metabolism 1998;47:384–90.
39. Anderssen SA, Hjermann I, Urdal P, Torjesen PA, Holme I. Improved carbohydrate metabolism after
physical training and dietary intervention in individuals with the “atherothrombogenic syndrome”. Oslo
Diet and Exercise Study (ODES). A randomized trial. J Intern Med 1996;240:203–9.
40. Singh RB, Singh NK , Rastogi SS , Mani UV, Niaz MA. Effects of diet and lifestyle changes on
atherosclerotic risk factors after 24 weeks on the Indian Diet Heart Study. Am J Cardiol 1993;71:1283–8.
41. Niskanen L, Laaksonen DE, Punnonen K, Mustajoki P, Kaukua J, Rissanen A. Changes in sex hormone-
binding globulin and testosterone during weight loss and weight maintenance in abdominally obese
men with the metabolic syndrome. Diabetes Obes Metab 2004;6:208–15.
42. Brook RD, Bard RL, Glazewski L, et al. Effect of short-term weight loss on the metabolic syndrome
and conduit vascular endothelial function in overweight adults. Am J Cardiol 2004;93:1012–6.
43. Esposito K, Marfella R, Ciotola M, et al. Effect of a mediterranean-style diet on endothelial dysfunction
and markers of vascular inflammation in the metabolic syndrome: a randomized trial. JAMA
2004;292:1440–6.
44. Poppitt SD, Keogh GF, Prentice AM, et al. Long-term effects of ad libitum low-fat, high-carbohydrate
diets on body weight and serum lipids in overweight subjects with metabolic syndrome. Am J Clin
Nutr 2002;75:11–20.
45. Higgins M, Kannel W, Garrison R, Pinsky J, Stokes J, III. Hazards of obesity – the Framingham
experience. Acta Med Scand Suppl 1988;723:23–36.
46. Knowler WC, Barrett-Connor E, Fowler SE, et al. Reduction in the incidence of type 2 diabetes with
lifestyle intervention or metformin. N Engl J Med 2002;346:393–403.
47. Hu FB. Sedentary lifestyle and risk of obesity and type 2 diabetes. Lipids 2003;38:103–8.
48. Hu FB, Manson JE, Stampfer MJ, et al. Diet, lifestyle, and the risk of type 2 diabetes mellitus in women.
N Engl J Med 2001;345:790–7.
158 Yannakoulia et al.
49. Stampfer MJ, Hu FB, Manson JE, Rimm EB, Willett WC. Primary prevention of coronary heart disease
in women through diet and lifestyle. N Engl J Med 2000;343:16–22.
50. Huang Z, Willett WC, Manson JE, et al. Body weight, weight change, and risk for hypertension in
women. Ann Intern Med 1998;128:81–8.
51. Neter JE, Stam BE, Kok FJ, Grobbee DE, Geleijnse JM. Influence of weight reduction on blood
pressure: a meta-analysis of randomized controlled trials. Hypertension 2003;42:878–84.
52. Manson JE, Colditz GA, Stampfer MJ, et al. A prospective study of maturity-onset diabetes mellitus
and risk of coronary heart disease and stroke in women. Arch Intern Med 1991;151:1141–7.
53. Visser M, Bouter LM, McQuillan GM, Wener MH, Harris TB. Elevated C-reactive protein levels in
overweight and obese adults. JAMA 1999;282:2131–5.
54. Albert MA, Ridker PM. The role of C-reactive protein in cardiovascular disease risk. Curr Cardiol Rep
1999;1:99–104.
55. Morrow DA, Ridker PM. C-Reactive protein, inflammation, and coronary risk. Med Clin North Am
2000;84:149–61, ix.
56. Ridker PM, Hennekens CH, Buring JE, Rifai N. C-Reactive protein and other markers of inflammation
in the prediction of cardiovascular disease in women. N Engl J Med 2000;342:836–43.
57. Bougoulia M, Triantos A, Koliakos G. Effect of weight loss with or without orlistat treatment
on adipocytokines, inflammation, and oxidative markers in obese women. Hormones (Athens)
2006;5:259–69.
58. Blair SN, Kohl HW, III, Paffenbarger RS, Jr., Clark DG, Cooper KH, Gibbons LW. Physical fitness
and all-cause mortality. A prospective study of healthy men and women. JAMA 1989;262:2395–401.
59. Wei M, Kampert JB, Barlow CE, et al. Relationship between low cardiorespiratory fitness and mortality
in normal-weight, overweight, and obese men. JAMA 1999;282:1547–53.
60. Wessel TR, Arant CB, Olson MB, et al. Relationship of physical fitness vs body mass index with
coronary artery disease and cardiovascular events in women. JAMA 2004;292:1179–87.
61. Orakzai RH, Orakzai SH, Nasir K, et al. Association of increased cardiorespiratory fitness with
low risk for clustering of metabolic syndrome components in asymptomatic men. Arch Med Res
2006;37:522–8.
62. Simonelli C, Eaton RP. Reduced triglyceride secretion: a metabolic consequence of chronic exercise.
Am J Physiol 1978;234:E221–7.
63. Simonelli C, Eaton RP. Cardiovascular and metabolic effects of exercise: the strong case for conditioning.
Postgrad Med 1978;63:71–7.
64. Tsekouras YE, Yanni AE, Bougatsas D, Kavouras SA, Sidossis LS. A single bout of brisk walking
increases basal very low-density lipoprotein triacylglycerol clearance in young men. Metabolism
2007;56:1037–43.
65. Duncan GE, Perri MG, Theriaque DW, Hutson AD, Eckel RH, Stacpoole PW. Exercise training, without
weight loss, increases insulin sensitivity and postheparin plasma lipase activity in previously sedentary
adults. Diabetes Care 2003;26:557–62.
66. Goodpaster BH, He J, Watkins S, Kelley DE. Skeletal muscle lipid content and insulin resistance:
evidence for a paradox in endurance-trained athletes. J Clin Endocrinol Metab 2001;86:5755–61.
67. Ring-Dimitriou S, Paulweber B, von Duvillard SP, et al. The effect of physical activity and physical
fitness on plasma adiponectin in adults with predisposition to metabolic syndrome. Eur J Appl Physiol
2006;98:472–81.
68. Nassis GP, Papantakou K, Skenderi K, et al. Aerobic exercise training improves insulin sensitivity
without changes in body weight, body fat, adiponectin, and inflammatory markers in overweight and
obese girls. Metabolism 2005;54:1472–9.
69. Ascherio A, Katan MB, Zock PL, Stampfer MJ, Willett WC. Trans fatty acids and coronary heart
disease. N Engl J Med 1999;340:1994–8.
70. Toft I, Bonaa KH, Ingebretsen OC, Nordoy A, Jenssen T, Effects of n-3 polyunsaturated fatty acids on
glucose homeostasis and blood pressure in essential hypertension. A randomized, controlled trial. Ann
Intern Med 1995;123:911–8.
71. Glauber H, Wallace P, Griver K, Brechtel G. Adverse metabolic effect of omega-3 fatty acids in non-
insulin-dependent diabetes mellitus. Ann Intern Med 1988;108:663–8.
Chapter 8 / Diet and Exercise in the Prevention and Management of the Metabolic Syndrome 159
72. Popp-Snijders C, Schouten JA, Heine RJ, van der Meer J, van der Veen EA. Dietary supplementation
of omega-3 polyunsaturated fatty acids improves insulin sensitivity in non-insulin-dependent diabetes.
Diabetes Res 1987;4:141–7.
73. Vessby B, Unsitupa M, Hermansen K, et al. Substituting dietary saturated for monounsaturated fat impairs
insulin sensitivity in healthy men and women: The KANWU Study. Diabetologia 2001;44:312–9.
74. Salmeron J, Hu FB, Manson JE, et al. Dietary fat intake and risk of type 2 diabetes in women. Am J
Clin Nutr 2001;73:1019–26.
75. Montoya MT, Porres A, Serrano S, et al. Fatty acid saturation of the diet and plasma lipid concentrations,
lipoprotein particle concentrations, and cholesterol efflux capacity. Am J Clin Nutr 2002;75:484–91.
76. Willett W, Manson J, Liu S. Glycemic index, glycemic load, and risk of type 2 diabetes. Am J Clin
Nutr 2002;76:274S–80S.
77. Liu S, Manson JE, Buring JE, Stampfer MJ, Willett WC, Ridker PM. Relation between a diet with a
high glycemic load and plasma concentrations of high-sensitivity C-reactive protein in middle-aged
women. Am J Clin Nutr 2002;75:492–8.
78. Liu S, Manson JE, Stampfer MJ, et al. Dietary glycemic load assessed by food-frequency question-
naire in relation to plasma high-density-lipoprotein cholesterol and fasting plasma triacylglycerols in
postmenopausal women. Am J Clin Nutr 2001;73:560–6.
79. Ludwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardio-
vascular disease. JAMA 2002;287:2414–23.
80. Nordmann AJ, Nordmann A, Briel M, et al. Effects of low-carbohydrate vs low-fat diets on weight
loss and cardiovascular risk factors: a meta-analysis of randomized controlled trials. Arch Intern Med
2006;166:285–93.
81. Abbasi F, McLaughlin T, Lamendola C, et al. High carbohydrate diets, triglyceride-rich lipoproteins,
and coronary heart disease risk. Am J Cardiol 2000;85:45–8.
82. Chiasson JL, Josse RG, Gomis R, Hanefeld M, Karasik A, Laakso M. Acarbose for prevention of type
2 diabetes mellitus: the STOP-NIDDM randomised trial. Lancet 2002;359:2072–7.
83. Chiasson JL, Josse RG, Gomis R, Hanefeld M, Karasik A, Laakso M. Acarbose treatment and the risk
of cardiovascular disease and hypertension in patients with impaired glucose tolerance: the STOP-
NIDDM trial. JAMA 2003;290:486–94.
84. Davies MJ, Baer DJ, Judd JT, Brown ED, Campbell WS, Taylor PR. Effects of moderate alcohol in-
take on fasting insulin and glucose concentrations and insulin sensitivity in postmenopausal women:
a randomized controlled trial. JAMA 2002;287:2559–62.
85. Gigleux I, Gagnon J, St-Pierre A, et al. Moderate alcohol consumption is more cardioprotective in men
with the metabolic syndrome. J Nutr 2006;136:3027–32.
86. Klatsky AL. Alcohol and cardiovascular disease – more than one paradox to consider. Alcohol and
hypertension: does it matter? Yes. J Cardiovasc Risk 2003;10:21–4.
87. Orchard TJ, Temprosa M, Goldberg R, et al. The effect of metformin and intensive lifestyle interven-
tion on the metabolic syndrome: the Diabetes Prevention Program randomized trial. Ann Intern Med
2005;142:611–9.
88. Lindstrom J, Louheranta A, Mannelin M, et al. The Finnish Diabetes Prevention Study (DPS): lifestyle
intervention and 3-year results on diet and physical activity. Diabetes Care 2003;26:3230–6.
89. Dattilo AM, Kris-Etherton PM. Effects of weight reduction on blood lipids and lipoproteins: a meta-
analysis. Am J Clin Nutr 1992;56:320–8.
90. Hubbard RS, Beck EC. Changes in the glucose tolerance of obese subjects after weight reduction.
J Clin Invest 1939;18:783–9.
91. Kukkonen-Harjula KT, Borg PT, Nenonen AM, Fogelholm MG. Effects of a weight maintenance pro-
gram with or without exercise on the metabolic syndrome: a randomized trial in obese men. Prev Med
2005;41:784–90.
92. Appel LJ, Sacks FM, Carey VJ, et al. Effects of protein, monounsaturated fat, and carbohydrate intake
on blood pressure and serum lipids: results of the OmniHeart randomized trial. JAMA 2005;294:
2455–64.
93. Kris-Etherton PM, Pearson TA, Wan Y, et al. High-monounsaturated fatty acid diets lower both plasma
cholesterol and triacylglycerol concentrations. Am J Clin Nutr 1999;70:1009–15.
160 Yannakoulia et al.
94. Wannamethee SG, Shaper AG, Whincup PH. Modifiable lifestyle factors and the metabolic syndrome
in older men: Effects of lifestyle changes. J Am Geriatr Soc 2006;54:1909–14.
95. Muzio F, Mondazzi L, Harris WS, Sommariva D, Branchi A. Effects of moderate variations in the
macronutrient content of the diet on cardiovascular disease risk factors in obese patients with the
metabolic syndrome. Am J Clin Nutr 2007;86:946–51.
96. Lien LF, Brown AJ, Ard JD, et al. Effects of PREMIER lifestyle modifications on participants with
and without the metabolic syndrome. Hypertension 2007;50:609–16.
97. Corcoran MP, Lamon-Fava S, Fielding RA. Skeletal muscle lipid deposition and insulin resistance:
effect of dietary fatty acids and exercise. Am J Clin Nutr 2007;85:662–77.
98. Katzmarzyk PT, Leon AS, Wilmore JH, et al. Targeting the metabolic syndrome with exercise: evidence
from the HERITAGE Family Study. Med Sci Sports Exerc 2003;35:1703–9.
99. Dumortier M, Brandou F, Perez-Martin A, Fedou C, Mercier J, Brun JF. Low intensity endurance
exercise targeted for lipid oxidation improves body composition and insulin sensitivity in patients with
the metabolic syndrome. Diabetes Metab 2003;29:509–18.
100. Votruba SB, Horvitz MA, Schoeller DA. The role of exercise in the treatment of obesity. Nutrition
2000;16:179–88.
101. Fenkci S, Sarsan A, Rota S, Ardic F. Effects of resistance or aerobic exercises on metabolic parameters
in obese women who are not on a diet. Adv Ther 2006;23:404–13.
102. Johnson JL, Slentz CA, Houmard JA, et al. Exercise training amount and intensity effects on meta-
bolic syndrome (from Studies of a Targeted Risk Reduction Intervention through Defined Exercise).
Am J Cardiol 2007;100:1759–66.
103. Anderssen SA, Carroll S, Urdal P, Holme I. Combined diet and exercise intervention reverses the
metabolic syndrome in middle-aged males: results from the Oslo Diet and Exercise Study. Scand J
Med Sci Sports 2007;17:687–95.
104. Jakicic JM, Otto AD. Physical activity considerations for the treatment and prevention of obesity.
Am J Clin Nutr 2005;82:226S–9S.
105. Johannsen DL, Redman LM, Ravussin E. The role of physical activity in maintaining a reduced
weight. Curr Atheroscler Rep 2007;9:463–71.
106. Schoeller DA, Shay K, Kushner RF. How much physical activity is needed to minimize weight gain in
previously obese women? Am J Clin Nutr 1997;66:551–6.
107. McManus K, Antinoro L, Sacks F. A randomized controlled trial of a moderate-fat, low-energy diet
compared with a low fat, low-energy diet for weight loss in overweight adults. Int J Obes Relat Metab
Disord 2001;25:1503–11.
108. Yannakoulia M. Eating behavior among type 2 diabetic patients: a poorly recognized aspect in a
poorly controlled disease. Rev Diabet Stud 2006;3:11–6.
109. Oh EG, Hyun SS, Kim SH, et al. A randomized controlled trial of therapeutic lifestyle modification in
rural women with metabolic syndrome: a pilot study. Metabolism 2008;57:255–61.
9 Diet and Physical Activity
in Cancer Prevention
Alicja Wolk
KEY POINTS
• Cancer confers a major disease burden worldwide, especially in affluent societies.
• Cancer incidence and mortality between low risk and high risk countries differs several-fold.
• These differences are ascribed such environmental factors as lifelong dietary behaviors,
physical inactivity, weight gain, alcohol consumption, and the use of tobacco.
• Through a healthy diet, optimal levels of physical activity and by maintaining normal body
weight, a large proportion of cancers may be prevented.
Key Words: Cancer, Diet, Food consumption, Incidence, Mortality, Physical activity,
Obesity, Prevention, Recommendations, Trends
1. INTRODUCTION
Cancer confers a major disease burden worldwide, but there are marked geographical
variations in cancer incidence overall and in cancers of specific organ sites. Worldwide,
approximately 10 million people are diagnosed with cancer annually, and more than
6 million die of the disease every year; currently over 22 million people in the world are
cancer patients. The total cancer burden is highest in affluent societies, mainly due to a
high incidence of tumors associated with Western lifestyle and smoking, i.e., tumors of
the prostate, breast, colorectum, and lung (1). Cancer incidence and mortality between
low risk and high risk countries differs by several fold.
2. TEMPORAL CHANGES IN CANCER INCIDENCE AND MORTALITY
Trends for cancer mortality during 1950–2000 and cancer incidence in 2002 for the
United States, Europe, and Japan are presented in Figs. 1 and 2. Cancer incidence and
mortality have been steadily rising throughout the century in most areas of the world.
However, over the last few years in North America and in Western Europe, some decline
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_9,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
161
162 Wolk
130
Mortality
120
110
Rate per 100 000
100
90
80
70
60
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000
Greece Japan Sweden USA
400
Year 2002
350
Incidence Mortality
300
Rate per 100 000
250
200
150
100
50
Greece Sweden USA Japan
Fig. 1. Time trends in mortality from all cancer and incidence rates of all cancer in 2002 among
women.
in cancer mortality has been observed. Thus, age-standardized cancer mortality rates
for all neoplasms in the USA declined by 3.1% in both sexes combined between 1990
and 1995 (1). Approximately half of the decline was attributed to the leveling of lung
and other tobacco-related cancer epidemics, and the rest to several factors, including
reduced exposure to occupational carcinogens, prevention and early diagnosis, and improved
treatment. In Europe as well as in North America and Japan, between 80 and 90% of
lung cancers in men, and between 55 and 80% of lung cancers in women, are attributable
to cigarette smoking. Taking into account all tobacco-related cancers, between 25 and
30% of all cancers in Europe and the USA are due to tobacco smoking. Because of the
length of the latency period, tobacco-related cancers observed today are mainly related
to cigarette smoking patterns several decades ago (1). Another major factor, identified
almost three decades ago as a factor contributing to cancer risk, is diet (2).
Comparing the incidence and mortality rates between the different countries we have
to keep in mind that Greek data may be less reliable than Swedish, and the data from the
United States and from Japan are reasonably reliable. The Greek data may overestimate
Chapter 9 / Diet and Physical Activity in Cancer Prevention 163
180
Mortality
170
160
Rate per 100 000 150
140
130
120
110
100
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000
Greece Japan Sweden USA
500
Year 2002
450
Incidence Mortality
400
Rate per 100 000
350
300
250
200
150
100
Greece Sweden USA Japan
Fig. 2. Time trends in mortality from all cancer and incidence rates of all cancer in 2002 among
men.
actual rates, because regional registries exist in the more developed regions that are usually
characterized by higher cancer rates (3).
Later we present time trends for prostate, breast, and colorectal cancer mortality
between 1950 and 2000 as well as incidence of these cancer sites in 2002 for the four
chosen countries representing different geographical regions (Figs. 3–5). The differences
between Japan and Sweden as well as the USA are striking for prostate and breast cancer
incidence and mortality, with Sweden having the highest and still increasing prostate
cancer mortality (4).
While breast cancer mortality is decreasing in the USA and Sweden, and there is a
suggestion that the increasing trend in Greece has changed, the opposite trend is seen in
Japan. The difference in mortality rates between the USA and Japan has changed from
almost five-fold in the 1950s to about 2.5-fold in 2000.
Mortality rates for colon cancer in the USA, although systematically decreasing since the
mid 1980s, are still higher than in Japan and Greece where rates continue to increase.
164 Wolk
30
Mortality
25
Rate per 100 000
20
15
10
5
0
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000
Greece Japan Sweden USA
160
Year 2002
140
Incidence Mortality
120
Rate per 100 000
100
80
60
40
20
0
Greece Sweden USA Japan
Fig. 3. Time trends in mortality rates from prostate cancer and incidence rates of prostate cancer
in 2002.
30
Mortality
25
Rate per 100 000
20
15
10
5
0
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000
Greece Japan Sweden USA
Fig. 4. Time trends in mortality rates from breast cancer and incidence rates of breast cancer in
2002.
Chapter 9 / Diet and Physical Activity in Cancer Prevention 165
140
Year 2002
120
Incidence Mortality
100
Rate per 100 000
80
60
40
20
0
Greece Sweden USA Japan
Fig. 4. (continued)
16
Mortality
14
12
Rate per 100 000
10
8
6
4
2
0
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000
Greece Japan Sweden USA
50
Year 2002
45
Incidence Mortality
40
35
Rate per 100 000
30
25
20
15
10
5
0
Greece Sweden USA
Fig. 5. Time trends in mortality rates from colon cancer and incidence rates of colorectal cancer
in women and men in 2002.
166 Wolk
3. MODIFIABLE CAUSES OF CANCER
Already in 1964, an expert committee of the World Health Organization concluded
that many common fatal cases of cancer could be potentially prevented by changes
in lifestyle and other environmental factors, including dietary deficiencies, hormonal
factors, and some environmental carcinogens (5). On the basis of the epidemiological
observation that migrants tend to acquire the cancer rates of their new country, Doll and
Peto concluded that differences in cancer rates can be attributed in part to environmental
factors such as smoking, diet, and others.
On the basis of comparisons of high and low incidence countries, they concluded
that 75–80% of cancers diagnosed in the United States in 1970 theoretically could have
been avoided (2). Their highest estimates were for poor dietary habits (approximately
35%) and smoking (30%), as shown in Fig. 6.
The question was what made the United States population different from low risk
populations, at that time. The question why the US has higher cancer incidence rates
than Greece, Japan, or Sweden is still not fully answered. The environmental factors that
differ between these countries are many and include mainly lifelong dietary behaviors,
physical inactivity, lifelong weight gain, alcohol consumption, and the use of tobacco.
Although the conclusion by Doll and Peto was provocative at that time, because of
limited data from analytical and rigorously performed epidemiological studies, it is still
true today, more than 25 years later.
Accumulated evidence from thousands of observational epidemiological studies
have confirmed the contribution of specific lifestyle factors to the etiology of cancer
and have expanded the list of cancer risk factors to include also obesity and physical
inactivity. The previously estimated 75–80% reduction in cancer burden was a theoretical
maximum, and Doll and Peto acknowledged that it was rather unlikely that any society
could change lifestyle enough – even over many years – to decrease cancer incidence
by this amount. However, the new estimates indicate that more than 50% of all cancer
Fig. 6. Proportions of cancer attributed to nongenetic factors. Estimated proportions that could
have been avoided in each category of factors as estimated by Doll and Peto (2).
Chapter 9 / Diet and Physical Activity in Cancer Prevention 167
cases could be prevented by achievable changes (6). Evidence indicates that in the
United States (Fig. 7), obesity accounts for some 15% of all cancer cases, physical
inactivity for 5% of cases, poor diet for 10–25% of cases, alcohol consumption for 4%
of cancer cases, and tobacco use for 30% (7).
For the great majority of people who do not use tobacco, weight control, dietary
choices, and the levels of physical activity are the most important modifiable determinants
of cancer risk (8–10). Although genetic factors influence the risk of cancer, most of the
variations in cancer risk across populations and among individuals are due to factors
that are not inherited (11,12). Such modifiable lifestyle-related factors as no smoking,
maintaining a healthy weight, staying physically active throughout life, and consuming
a healthy diet can substantially reduce one’s lifetime risk for developing cancer (10,13).
It is important to point out that the same healthy behaviors are also associated with
reduced risk of developing cardiovascular disease.
As is shown in Figs. 3–5, cancer rates especially for prostate and breast cancer,
differ several fold between Western and Asian countries, similar to differences in
food consumption (Fig. 8a–d). Differences in food patterns between the four countries
described in this chapter are large. In Greece there is much higher per capita availability
of vegetables, roots and tubers, fruits, pulses, and nuts than in the three other countries
(Fig. 8a, b). In Sweden there is the highest per capita availability of milk and coffee
(Fig. 8c, d); Japan is leading regarding the per capita availability of fish and tea (Fig.
8c, d), and USA is leading in red meat availability (Fig. 8c).
Differences in prevalence of obesity between the four countries are several fold,
with Japan having the lowest and USA the highest prevalence (Fig. 9). Overweight and
obesity have reached epidemic proportions globally along with an adoption of a life-
style characterized by a combination of excessive food intake and inadequate physical
activity. The dramatic rise in prevalence of obesity and increasing inactivity has been
accompanied by increases in the incidence and prevalence of type 2 diabetes. There is
accumulating evidence that diabetes is associated with an increased risk for cancer at
several sites (14).
Fig. 7. Proportion of cancer attributable to modifiable lifestyle factors in the United States
according to recent estimates.
a
Cereals
700
600
Food quantity/day/capita (g)
500
400
300
200
100
0
90
92
94
96
98
00
02
04
19
19
19
19
19
20
20
20
Roots and tubers
350
300
Food quantity/day/capita (g)
250
200
150
100
50
0
90
92
94
96
98
00
02
04
19
19
19
19
19
20
20
20
Vegetables
800
700
Food quantity/day/capita (g)
600
500
400
300
200
100
0
90
2
4
6
8
0
2
4
9
9
9
9
0
0
0
19
19
19
19
19
20
20
20
Fig. 8. (a) Time trends in mean per capita availability (in g/day) of selected food groups – cereals,
roots and tubers, and vegetables – in Greece, Sweden, USA and Japan. (b) Time trends in mean
per capita availability (in g/day) of selected food groups – fruits and berries, pulses, and nuts – in
Greece, Sweden, USA, and Japan. (c) Time trends in mean per capita availability (in g/day) of
selected food groups – fish, red meat, and milk – in Greece, Sweden, USA, and Japan. (d) Time
trends in mean per capita availability (in g/day) of selected food groups – coffee, tea and matè,
and sugar crops – in Greece, Sweden, USA, and Japan.
b
Fig. 8. (continued)
Food quantity/day/capita (g) Food quantity/day/capita (g) Food quantity/day/capita (g)
0
2
4
6
8
10
12
14
16
18
20
0
100
200
300
400
500
600
700
800
0
5
10
15
20
25
30
35
19 19 19
90 90 90
19 19 19
92 92 92
19 19 19
94 94 94
19 19 19
96 96 96
Nuts
19 19 19
Pulses
98 98 98
Chapter 9 / Diet and Physical Activity in Cancer Prevention
Fruits and Berries
20 20 20
00 00 00
20 20 20
02 02 02
20 20 20
04 04 04
169
170
c
Fig. 8. (continued)
Food quantity/day/capita (g) Food quantity/day/capita (g) Food quantity/day/capita (g)
0
100
200
300
400
500
600
700
800
900
1000
0
50
100
150
200
250
0
50
100
150
200
250
19 19 19
90 90 90
19 19 19
92 92 92
19 19 19
94 94 94
19 19 19
96 96 96
Fish
19 19 19
98 98 98
Red Meat
Milk, whole, fresh
20 20 20
00 00 00
20 20 20
02 02 02
20 20 20
04 04 04
Wolk
d
Fig. 8. (continued)
Food quantity/day/capita (g) Food quantity/day/capita (g) Food quantity/day/capita (g)
0
0.5
1
1.5
2
2.5
3
3.5
100
200
300
400
500
600
700
800
900
0
0
5
10
15
20
25
30
35
19 19 19
90 90 90
19
91
19 19 19
92 92 92
19
93
19 19 19
94 94 94
19
95
19 19 19
96 96 96
19
97
19 19 19
98 98 98
Sugarcrops
19
Chapter 9 / Diet and Physical Activity in Cancer Prevention
Tea and Maté
Coffee, green
99
20 20 20
00 00 00
20
01
20 20 20
02 02 02
20
03
20 20 20
04 04 04
171
172 Wolk
Obesity Prevalence
35
30
25
Prevalence (%)
20
15
10
Greece
5 Sweden
USA
Japan
0
1980 1990 2000 2001 2002 2003 2004
Year
Fig. 9. Time trends in obesity prevalence among adult women and men in four countries from
different geographic regions.
Differences in physical activity and inactivity between the countries described in this
chapter are presented in Fig. 10. As shown in Fig. 11a, b, temporal changes in decreasing
physical activity between the 1930s and the 1990s among Swedish women and men are
very striking in all age groups (16,17). Especially pronounced is the decreasing demand for
occupational physical activity and decreasing energy expenditure related to walking.
Furthermore, there are differences between the four countries in alcohol consumption
and tobacco use (Fig. 12). Temporal changes in these modifiable lifestyle factors that
have been shown to be associated with cancer risk – namely food consumption patterns,
obesity, physical inactivity, smoking and alcohol – are paralleled by changes in cancer
incidence. Prevalence of smoking in Sweden and USA has been decreasing in both
women and men (Fig. 12). Policy and community interventions have been especially
successful in Swedish men.
4. DIET AND CANCER
This review on diet and cancer is limited to the three cancer sites with the highest
incidence in developed countries.
4.1. Prostate Cancer
Prostate cancer (PC) is the most frequent cancer among men in North America as
well as in Northern and Western Europe. Causes of the disease are essentially unknown,
although it is estimated in studies of twins that hereditability of PC is approximately
Greece
Sweden
Japan
Fig. 10. Prevalence of physical inactivity (unspecified) by age groups in Greece, Sweden, and
Japan (15).
174 Wolk
a Total physical activity -Women
Total physical activity -Men
49
48
47
46
MET-hours/day
45
44
43
42
41
Age 15
40 Age 30
Age 50
39
6
1
6
6
1
6
1
6
1
6
1
7
51
-3
-4
-4
-5
-6
-6
-7
-7
-8
-8
-9
-9
7-
32
37
42
52
57
62
67
72
77
82
87
92
4
19
19
19
19
19
19
19
19
19
19
19
19
19
Fig. 11. (a) Temporal trends in physical activity among Swedish adolescents, women and men.
(b) Temporal trends in specific types of physical activity among Swedish adolescent girls and
boys, women and men.
42%, the highest of all studied cancers (11). There is approximately a 40-fold difference
in the reported incidence and a 12-fold difference in mortality of PC between various
geographic areas and populations (21). Diet is suspected to play a major role in the
initiation, promotion, and progression of PC. Among the dietary factors that have
Chapter 9 / Diet and Physical Activity in Cancer Prevention 175
b Specific type of physical activity - Women
Occupation Walking/bicycling Housework Inactive leisure-time Exercise
17 17 17
15 15 15
13 13 13
MET-hours / day
11 11 11
9 9 9
7 7 7
5 5 5
3 3 3
1 1 1
-71
-36
-41
-46
-51
-56
19 61
-66
-51
-56
-61
-66
-71
-76
-81
-76
-81
-86
-91
-97
-
67
29
37
42
47
52
57
62
47
52
57
62
67
72
77
72
77
82
87
92
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
Age 15 Age 30 Age 50
Specific type of physical activity - Men
Occupation Walking/bicycling Housework Inactive leisure-time Exercise
17
16
MET-hours / day
15
14
13
12
5 11
4
MET-hours / day
3
2
1
0
6
1
6
1
6
1
6
1
6
1
6
1
6
1
1
6
1
6
1
7
-3
-4
-4
-5
-5
-6
-6
-5
-5
-6
-6
-7
-7
-8
-7
-7
-8
-8
-9
-9
32
37
42
47
52
57
62
47
52
57
62
67
72
77
67
72
77
82
87
92
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
Age 15 Age 30 Age 50
Fig. 11. (continued)
most consistently been associated with increased risk of PC development are meat and
milk products.
High consumption of meat, particularly red or processed meat, generally is associated
with moderate to severe increases in risk of PC by 30 or more percent in most studies
(22), although conflicting evidence exists (23). Those few studies that have separately
analyzed the association, not only with total prostate cancer but also with advanced and
metastatic tumors, have reported even higher risk estimates for the advanced stages
176 Wolk
Fig. 12. Time trends in prevalence of smoking among women and men in four countries (18–20).
of the disease (24). A two-fold increase was found for advanced cancer and a 2.2-fold
increase in metastatic cancer compared with 40–50% increase for total PC. These results
suggest a possible role of meat in the progression of PC. The mechanisms by which
meat consumption might affect the risk of prostate cancer remain unknown. It has been
speculated that the observed positive association may reflect the high intake of fat,
especially that of total fat; in Asian countries with a low incidence of the disease, total
intake of fat is much lower than in countries with high incidence, although findings of
Chapter 9 / Diet and Physical Activity in Cancer Prevention 177
total dietary fat and specific fat types are mixed (24). Another speculation is that meat
that is grilled or pan-fried at high temperatures contains heterocyclic amines that have
been found to contain carcinogens in animal studies on rat prostates (25). A recent
prospective study has indeed shown that an average consumption of more than 10 g/
day of very well done meat, compared with no consumption at all, is associated with a
statistically significant 70% increased risk of incident prostate cancer (26). Red meat is
a major source of zinc, which is known to be essential for testosterone synthesis (27).
The use of zinc supplements of more than 100 mg/day and for more than 10 years was
associated with more than two-fold increase in risk of PC compared with nonusers (28).
High consumption of red meat and a high zinc and protein intake was also associated
with a higher circulating concentration of insulin-like growth factor 1 (IGF-1) (29).
Interestingly, high IGF-1 levels have consistently been associated with high incidence
of PC (30).
Milk products also appear to consistently be associated with increased risk of PC.
Those few studies that have analyzed advanced and metastasized PC separately suggested
that the association might be stronger for the more advanced cancers than for all PC
(22). This might indicate a possible role of dairy products in the progression of this
neoplasm. The mechanisms behind these observed associations are not known. Many
studies indicate that calcium, the main dietary component of dairy products, may play
an important role in PC development. In the Health Professionals follow-up study, men
who consumed more than 2,000 mg/day of calcium had an approximately five-fold
increased risk of developing metastatic and fatal PC compared with those consuming less
than 500 mg/day (31,32). High consumption of low-fat milk has been associated with a
higher concentration of circulating IGF-1 (33). Another possibility is that branched fatty
acids present mainly in milk fat, and also in beef, may up-regulate the a-methylacyl Co
A racemase (AMACR) gene, previously shown to be over-expressed in PC tumors, and
not in healthy prostates (34).
There are also other dietary factors that are thought to be protective. Although there
is a general health recommendation to eat five or more servings of fruits and vegetables
per day, the accumulated evidence does not support any reduced risk of prostate cancer
(35). However, several epidemiological studies have reported that some vegetables,
specifically tomatoes, and lycopene (the predominant carotenoid found in serum), from
tomatoes mainly, are associated with lower risk of PC. Indeed, a review of four studies of
serum lycopene and incidence of PC report a significant reduction in risk (25–80%) (36).
In a meta-analysis of 21 studies, high consumption of tomatoes resulted in a 10–20%
risk reduction (37). There is also a suggestion that other carotenoids lower the risk (24).
Several epidemiological studies have reported an inverse relationship with cruciferous
vegetables (specifically cabbage, broccoli, cauliflower, and brussel-sprouts) and the risk
of developing PC (24), whereas the European Prospective Investigation into Cancer
(EPIC) did not (38). In the Health Professionals follow-up study, an inverse association
was only observed for early stage cancer in younger men, suggesting that cruciferous
vegetables may be important early on in the carcinogenesis process (39). Anticarcino-
genic phytochemicals that are present in cruciferous vegetables (indole-3-carbinol and
isothiocyanates) can induce antioxidative enzymes and counteract oxidative damage.
They have also been shown to have proapoptotic, antiproliferative, and antimetastatic
properties in animal models of PC (40).
178 Wolk
Furthermore, other phytochemicals found in fruits and vegetables, tea, and red wine,
namely polyphenols and isoflavones, have been shown in experimental studies to have
antioxidant, antiproliferative, antiangiogenesic, or proapoptotic effects (24,41). Given
the promising results from in vitro and animal studies on these phytochemicals, epide-
miological studies are needed.
The most promising micronutrients regarding nutritional protective factors are
vitamin E and selenium. Vitamin E, an antioxidant found mainly in vegetable oil, nuts
and oils, has been observed to significantly reduce the risk for PC among smokers in a
Finnish intervention study (42). That study has shown that men receiving 50 mg/day of
supplemental vitamin E (a-tocopherol) had a 30–40% reduction in PC incidence and
mortality compared with men taking a placebo. Selenium is an essential micronutrient
present mainly in grains, fish, and eggs. The level of selenium in the soil determines
its level in the plants grown in that area. Therefore, any variation in the selenium levels
of food may be largely derived from the levels of the geographic area in which they
were grown. Selenium intake has been observed to predict a lower risk of PC in several
large prospective studies, but this is not always the case (22,43). High vs. low selenium
levels in nails or plasma resulted in a reduction of 50–65% in the risk of PC (44,45). In
the randomized Nutrition Prevention of Cancer Trial study, men taking supplemental
selenium had a 50% lower risk compared with the placebo group (46).
In recent years, a great deal of attention has been given to the so-called phytoestro-
gens. These phytochemicals with some estrogen-like activities are present in plant foods.
Most frequently studied are soy foods, but, Westerners traditionally consume other plant
foods containing so-called lignans (sources of which include flaxseed and rye), which
are also ascribed estrogen-like and anticarcinogenic properties (47,48). In a recent large
case-control study in Sweden, total or individual consumption of lignans or isoflavonoids
was not associated with PC. However, high total consumption of foods rich in lignans
and isoflavones was associated with moderate decrease in risk of PC (49).
There are several studies showing that fish consumption decreases PC incidence
and mortality (22,24,50). The mechanism behind this observation might be linked to
marine omega-3 fatty acids, a source of which is oily fish (salmon, mackerel, sardines,
and herring). Fish is also an additional source of selenium and vitamin D and is also
considered to have anticarcinogenic properties (51). However, it has to be noted that the
main source of vitamin D remains exposure to ultraviolet light.
4.2. Breast Cancer
Migration studies suggest that lifestyle, aside from genetics, is a key factor in breast
cancer risk. Breast cancer rates are rising globally in patterns that correspond with life-
style changes. Belief such as fatty foods cause breast cancer (52) while consumption
of vegetables and fruit reduce this risk have not confirmed (53). Instead, obesity
and disordered energy balance are proving to be important risk factors (54). Indirect
epidemiologic evidence suggests that diet in early life may matter most, possibly due
to increased mammary sensibility to carcinogens (55). Adult diet composition may also
play a role in breast neoplasia. Although dietary fat does not appear to influence breast
cancer risk (52,56), carbohydrate quality intake may prove to be important. Even moderate
alcohol consumption increases risk of breast cancer (57), yet this effect can be reduced
by an adequate folate intake (58,59).
Chapter 9 / Diet and Physical Activity in Cancer Prevention 179
In the Pooling Project on Diet and Cancer analysis, which included over 7,000
cases of breast cancer, no association between total fat and risk of breast cancer was
found (56). In recent analysis of the Nurses’ Health Study (NHS), a cohort of over
120,000 nurses, longtime exposure to dietary fat and the effect of time latency were
examined (60). In this study which included over 3,500 postmenopausal women, there
was no association between total fat intake and breast cancer, even after considering
various disease latencies up to 20 years. An association was observed only for a very
low and very high intake of fat (below 20% and above 50% of energy from fat) and
when tumor type was considered. Monounsaturated fat has been associated with lower
breast cancer risk in some studies (61,62), whereas animal fat has been associated
with higher risk (63). However, there was no association observed between poly- or
mono-saturated fat and breast cancer incidence in the Pooling Project (52,56). Overall,
substantial evidence demonstrates that adult consumption of fat does not increase the
risk of breast cancer.
Carbohydrates and carbohydrate quality, as measured by glycemic index or glycemic
load, have been positively associated with breast cancer risk in some case-control studies
(64). Yet, no overall associations of carbohydrate or carbohydrate quality and breast
cancer risk have been reported in prospective studies in adult diet. An inverse relation-
ship of high fiber intake to postmenopausal breast cancer risk was noted in a Swedish
prospective study (65), where the highest vs. the lowest quintile of fiber intake was
associated with a significant 42% lower risk. However, in most other prospective studies
the associations between dietary fiber and breast cancer were null (64).
Alcohol consumption increases risk of breast cancer in a dose-response manner;
each additional 10 g of alcohol consumed daily corresponds to a 9% (95% confidence
interval 4–13%) increase in breast cancer risk, according to the Pooling Project results
(57). In an updated analysis of the Nurses’ Health Study with over 5,300 cases, alcohol
intake as low as half a drink daily was statistically significantly associated with breast
cancer risk (66). This association was observed with a variety of alcoholic beverages
and drinking patterns. Estrogen levels increase significantly with consumption of one to
two alcoholic drinks daily (67), suggesting a potential mechanism through which alcohol
may increase the risk of breast cancer. In a Swedish prospective cohort of over 1,200
cases of invasive breast cancer with known estrogen and progesterone receptor status,
the association with alcohol seemed to be stronger for estrogen-positive breast cancer
types (68). High intake of folic acid, which is involved in DNA-methylation and repair,
has consistently been shown to minimize the excess risk of breast cancer associated with
regular alcohol consumption (58). Analysis of plasma folic acid levels confirmed this
mitigating effect, which is strongest in women who consume at least one drink daily (59).
The public health implications of this positive association between alcohol consumption
and breast cancer are complicated by the protective effect of moderate alcohol consump-
tion on cardiovascular disease and the overall reduction in total mortality (69). Women
who chose to consume alcohol regularly may benefit from a multivitamin containing
folic acid to lessen the risk of breast cancer (58).
Neither fruit nor vegetable consumption in adulthood seems to protect against overall
breast cancer. The Pooling Project analysis showed no effect of adult consumption of
fruit and vegetable consumption on breast cancer incidence (53). This lack of association
was recently confirmed in the EPIC cohort of ten European countries (70).
180 Wolk
No association between total, red or white meat consumption, or dairy products and
breast cancer was observed in the Pooling Project (71). Both calcium and vitamin D
were inversely related to risk of postmenopausal breast cancer; dietary calcium and
other components of dairy products were inversely related to risk of postmenopausal
breast cancer, especially among women with estrogen-positive tumors (72). Dietary
intake and plasma levels of vitamin D were associated with lower risk of breast cancer
in observational studies (73,74). In the Nurses’ Health Study, dietary carotenoids and
total vitamin A were associated with lower breast cancer risk only among premenopausal
women, especially in those who had a family history of breast cancer (75). However, no
overall association between intake of carotenoids and breast cancer was shown in other
prospective studies (64). In analysis of the Nurses’ Health Study cohort, a significant
inverse association between high plasma levels of a-carotene, β-carotene, lutein and
zeaxanthin, and total carotenoids and breast cancer risk was observed (76). These data
suggest that elevated serum carotenoids are associated with lower risk of breast cancer.
Prospective studies have not found significant overall associations between vitamin E,
vitamin C, or selenium and breast cancer (64). Clarifying the role of diet in breast
cancer etiology is important because there are few other factors to prevention. Obesity
and disordered energy balance are proving to be important risk factors.
4.3. Colorectal Cancer
Colorectal cancer (CRC) is the third most common cancer among men and women
combined in Sweden and the United States. Worldwide in 2002, approximately 1 million
new cases of cancer were diagnosed (9.4% of new cases of cancer) and 529,000 individuals
died from this malignancy (77). Incidence rates vary approximately 25-fold around the
world, with the highest rates in Japan, North America, and Europe. The international
differences and trends together with data from migrant studies imply that environmental
factors play an important role in the etiology of CRC. The 25-fold geographic variation
may be explained in large part by different dietary and other environmental factors.
There is considerable evidence that high consumption of red meat and processed meat
may increase the risk of CRC (78). In a quantitative assessment of the association between
red and processed meat consumption and CRC risk based on 15 prospective studies, there
was an observed 28% increased risk in the highest relative to the lowest category of red
meat consumption. Similarly, high vs. low processed meat consumption was associated
with a 20% increase in CRC risk (79). Dose-response meta-analysis showed a statistically
significant 31% increased CRC risk associated with each 120 g/day increment for red
meat consumption, and the statistically significant 11% increase in risk for each 30 g/day
increment of processed meats (79). The mechanisms behind these associations may
involve a combination of factors such as the content of fat, protein, and heme iron, and/
or meat preparation methods (for example, cooking in high temperature and preserv-
ing methods). The fat content of meat might influence the risk of CRC by increasing
the production of secondary bile acids, which may promote colon carcinogenesis (80).
However, epidemiologic studies have generally not shown a relation between fat intake
and risk of CRC (81). Red meat contains higher amounts of heme iron than white meat
(poultry and fish). Intake of heme iron was statistically significantly positively associ-
ated with the risk of CRC in an American prospective study (82) and in the Swedish
Mammography Cohort (83). Meta-analysis of prospective studies of poultry and chicken
Chapter 9 / Diet and Physical Activity in Cancer Prevention 181
indicated a potential inverse association; comparing the highest to the lowest category
of consumption a 12% decreased risk was indicated; there was no clear inverse
association of CRC with fish consumption (84). The relationship between processed
meat consumption and CRC may be partly due to N-nitroso-compounds (NOCs). An
alternative mechanism through which red meat consumption might increase the risk of
CRC is by increasing circulating insulin-like growth factor-1 levels. In a cross-sectional
study of Swedish men, we found a statistically significant positive relation between red
meat consumption and serum IGF-1; men in the highest quintile of red meat intake had
13% higher serum IGF-1 levels than men in the lowest quintile (29).
There is accumulating evidence that dairy products are associated with lower risk of
colorectal cancer. Dairy products are the major source of calcium and dietary vitamin
D in Sweden (85) and in the United States (86); milk products are fortified with vita-
min D in these countries. Milk products also contain other potentially anticarcinogenic
compounds, including conjugated linoleic acid (CLA) and sphingolipids (87,88). CLA
has been shown to inhibit CRC cancerogenesis in animal models (89). In the Swedish
Mammography Cohort, we observed statistically significant inverse association between
intakes of CLA and high-fat dairy foods (the main source of CLA) and risk of CRC
(90). The relationship between milk consumption and risk of CRC was examined in the
Pooling Project of Prospective Studies on Diet and Cancer in which the primary data
from ten cohort studies (in five countries) were pooled (91). The pooled results revealed
a statistically significant inverse association between milk consumption and CRC (P
trend < 0.001); compared with individuals in the lowest category of milk consumption
(<70 g/day), the multivariate relative risk for those in the highest category (³250 g/day)
was statistically significantly 15% lower. In the Cohort of Swedish Men, not included
in the Pooling Project, men in the highest category of milk consumption (³1.5 glass/
day) had a statistically significant 33% lower risk of CRC compared with those who
consumed less than two glasses of milk per week (92). The inverse association between
CRC and dairy products may be ascribed to calcium, vitamin D, CLA, sphingolipids,
and other components of milk.
Studies that have examined circulating 25-hydroxy vitamin D [25(OH)D] serum
concentrations and risk of colon and colorectal cancer have found reduced risk associated
with higher vitamin D concentrations. Meta-analysis of these studies indicated that people
in the highest category with the highest concentration of vitamin D had a significantly 54%
lower risk of CRC in comparison to the lowest category (84). Meta-analysis of prospective
studies based on intake of total vitamin D showed 21% statistically significantly decreased
risk in those in the highest vs. the lowest category of intake (84).
Calcium has been hypothesized to reduce the risk of CRC by binding secondary
bile acids and ionized fatty acids to form insoluble soaps in the colonic lumen, thereby
diminishing the potentially proliferative stimulus of these compounds on colonic mucosa (93).
Calcium may also directly influence the proliferative activity of the colonic mucosa and
may also influence differentiation and apoptosis (94). Some clinical trials have shown
that increased calcium intake could decrease colonic epithelial cell proliferation (95).
Additionally, in randomized trials, calcium supplementation reduces the recurrence
of colorectal adenoma (96,97) consistent with the role of calcium in the early stages
of carcinogenesis. The totality of evidence from laboratory studies, observational
epidemiological studies, and randomized trials of colorectal polyp recurrence supports
182 Wolk
the hypothesis that the high intake of calcium reduces the risk of CRC. In the Pooling
Project of Prospective Studies of Diet and Cancer, where data from ten cohorts were
analyzed together, the highest quintile when compared with the lowest quintile of
dietary calcium intake was associated with a statistically significant 14% lower risk
and total calcium intake (including calcium supplements) with a 22% lower risk (91).
In the Cohort of Swedish Men (not included in the Pooling Project), men in the highest
quartile (>1,445 mg calcium/day) compared with those in the lowest quartile (<956 mg/
day) had a statistically significant 32% lower risk (92).
Fruits and vegetables, besides being a rich source of dietary fiber, carotenoids, certain
vitamins (particularly folate and vitamin C), and magnesium contain numerous phyto-
chemicals that may have anticarcinogenic properties. Although the majority of about
30 case-control studies have found inverse associations between fruit and/or vegetable
consumption and CRC risk, findings from prospective cohort studies have been less
consistent (35). In a meta-analysis (98), the estimated relative risk for 100 g/day increase
in fruit consumption was decreased by 7% in case-control studies (statistically signifi-
cant) and by 4% in cohort studies (not reaching significance). The corresponding risk for
vegetable consumption was 13% in case-control studies (statistically significant) and 4%
(not significant) in cohort studies. In summary, the hypothesis that high consumption of
fruits and vegetables may reduce the risk of CRC has not been firmly established.
The idea that a high fiber diet might reduce the risk of CRC dates back to the early
1970s, when Burkit postulated that the low occurrence of CRC he observed in Southern
Africa was related to high fiber intake (99). Although the fiber hypothesis gained support
from a number of case-control studies from different countries, the findings of cohort
studies of dietary fiber intake in relation to risk of CRC have been inconsistent (100).
Findings from large prospective cohort studies provide some indications that dietary
fiber intake might be related in some way to risk of colon or rectal neoplasia; however,
results are not entirely consistent.
A meta-analysis of 12 case-control studies showed a statistically significant 28% reduc-
tion in risk of CRC for high vs. low coffee consumption (32). However, recent results
from large prospective cohort studies have not supported an association with coffee
consumption (101,102). In a meta-analysis of epidemiologic studies (13 case-control
and seven cohort studies) of tea drinking, there was no association with black tea and
a statistically significant 18% lower risk for green tea (based on four case-control and
four cohort studies); however, that inverse association was limited only to case-control
studies (103). The accumulated evidence does not support an association of coffee or
tea with risk of colorectal cancer.
5. OBESITY, PHYSICAL ACTIVITY, AND CANCER
Obesity is increasing at an alarming rate in the US, Europe, and all over the world,
and the increase in childhood obesity is particularly troublesome (104). Lifestyle factors
including diet, eating habits, levels of physical activity as well as inactivity are often
adopted during the early years of life. As childhood obesity is also strongly related to
obesity in adulthood, the best time to address the problem is early in life. Maintaining
normal weight is challenging nowadays. On the one hand, there is an abundance of
energy-rich foods that are often poor in nutrients, such as different types of fat-rich and
sugar-rich cakes and other sweets. On the other hand, there are decreasing needs and
Chapter 9 / Diet and Physical Activity in Cancer Prevention 183
opportunities for physical activity both at work and at leisure time. Such simple activity
as walking has been decreasing during the past several decades, in parallel with increas-
ing modernization (Fig. 11a–b).
Even though people actually need less and less energy due to the increasing seden-
tary lifestyle, there has been a tendency for portion sizes to increase over time (105).
The seriousness of these problems makes nutrition, physical inactivity, and obesity key
priorities in the prevention of major chronic diseases including cancer.
In 2002, the IARC Prevention Report on Weight Control and Physical Activity
concluded that obesity and lack of physical activity are major causes of cancer incidence
and mortality (9). The accumulated evidence indicated that obesity was directly associated
with risk of cancer at several organ sites including colon, breast (in postmenopausal
women), endometrium, esophagus, and kidney (9). Furthermore, data from the American
Cancer Society Cancer Prevention Study II, which followed more than 1 million men and
women during 16 years, also showed direct associations between obesity and mortality
from cancer of the prostate, pancreas, non-Hodgkin’s lymphoma, and myeloma (106).
The conclusion from this large prospective study was that 16–20% of cancer deaths among
American women and 14% of cancer deaths among men are attributable to obesity (107).
The IARC Prevention Report from 2002 also stated that there was accumulated
sufficient evidence to conclude that physical inactivity was linked to increased risk
of breast and colon cancer (9). In a recent systematic review of 19 cohort studies and
29 case-control studies, it was reported that there was strong evidence for an inverse
association between physical activity and postmenopausal breast cancer, but the evidence
was much weaker for premenopausal breast cancer (108). In postmenopausal women,
when comparing the highest with the lowest categories of physical activity, there were
risk reductions ranging from 20 to 80%. In about half of the methodologically higher-
quality studies, there was evidence for a dose-response relationship. Each additional
1 h of physical activity per week was associated with a 6% (95% confidence interval
3–8%) decrease in breast cancer risk. In a study of the California Teachers including over
110,000 women aged 20–79 years, strenuous long-term exercise activity was protective
against invasive and in situ breast cancers. However, the protective effect was limited to
estrogen receptor negative breast cancer (109).
We have recently reported that physical activity is also associated with decreased
risk of endometrial cancer, especially among obese women (110). Interestingly, among
diabetic women, who have two-fold increased risk, we observed that physical activity
can reduce the risk to a similar level as among women without diabetes (111). The
mechanisms by which physical activity may protect against breast and endometrial cancer
may involve body size, which affects estrogen exposure in postmenopausal women (112),
and serum hormone levels (113). Furthermore, physical activity may influence insulin
sensitivity (114) and growth factors (115), as well as adiponectin (116). Adiponectin
has been shown to be associated with decreased risk of breast (117), endometrial, and
other cancers (118).
Convincing epidemiological data support the role of physical activity in reducing
colon cancer risk (9,119). Meta-analysis of prospective studies (published through
October 2006) on leisure time physical activity and risk of colon cancer has shown
statistically significant 25% lower risk when comparing the highest to the lowest
category (78). In contrast to colon cancer, there was no association between physical
activity and risk of rectal cancer.
184 Wolk
6. GUIDELINES FOR CANCER PREVENTION
6.1. American Cancer Society Guidelines on Diet and Physical Activity
The American Cancer Society (ACS) publishes nutrition and physical activity guide-
lines to serve as a foundation for its communication policy and community strategies
and ultimately to affect dietary and physical activity patterns among Americans. These
guidelines, published every 5 years, represent the most current scientific evidence related
to dietary and activity patterns and cancer risk. The recent guidelines were updated in
October 2006. They are consistent with guidelines from the American Heart Associa-
tion (120) and the American Diabetes Association (121) for the prevention of coronary
heart disease and diabetes, as well as for general health promotion, as defined by the
Department of Health and Human Services’ 2005 Dietary Guidelines for Americans
(122). In the ACS guidelines, it is very clearly stated that the most important modifi-
able determinants of cancer risk among those who do not use tobacco are weight con-
trol, healthy diet, and appropriate levels of physical activity. Evidence suggests that one
third of cancers that occur in the USA each year can be attributed to diet and physical
activity habits. Healthy behavior such as maintaining healthy weight, staying physi-
cally active throughout life, and consuming a healthy diet can substantially reduce one’s
lifetime risk of developing cancer (10,13). The same behaviors are also associated with
decreased risk of developing cardiovascular disease. Recent ACS guidelines for cancer
prevention are presented in Table 1.
Table 1
American Cancer Society Guidelines on Nutrition and Physical Activity for Cancer
Prevention, Updated in October 2006 (123)
Guidelines on nutrition and physical activity for cancer prevention
Maintain a healthy weight throughout life
Balance caloric intake with physical activity
Avoid excessive weight gain throughout the life cycle
Achieve and maintain a healthy weight if currently overweight or obese
Adopt a physically active lifestyle
Adults: engage in at least 30 min of moderate to vigorous physical activity, above usual
activities, on 5 or more days of the week. Intentional physical activity is preferable for
45–60 min
Children and adolescents: engage in at least 60 min per day of moderate to vigorous
physical activity at least 5 days per week
Consume a healthy diet with an emphasis on plant sources
Choose food and beverages in amounts that help achieve and maintain a healthy weight
Eat five or more servings of a variety of vegetables and fruits each day
Choose whole grains in preference to processed (refined) grains
Limit consumption of processed and red meats
If you drink alcoholic beverages, limit consumption
Drink no more than one drink per day for women and two per day for men
Chapter 9 / Diet and Physical Activity in Cancer Prevention 185
6.2. World Cancer Research Fund International Guidelines
The mission of the World Cancer Research Fund (WCRF) global network, an alliance
of organizations dedicated to the prevention of cancer worldwide, is to raise aware-
ness that the risk of cancer is reduced by healthy food and nutrition, physical activity,
and weight management. WCRF supports research to develop and strengthen scientific
knowledge of the relation of food and nutrition, physical activity, and weight manage-
ment for cancer prevention.
The research and education programs of WCRF International and its national mem-
bers are based on the conclusions and recommendations of the WCRF and American
Institute for Cancer Research (AICR) Second Expert Report “Food, Nutrition, Physical
Activity, and the Prevention of Cancer: a Global Perspective,” which was published in
November 2007 (10). This report that summarized the accumulated knowledge on diet,
physical activity, and cancer was distributed throughout the world and acclaimed as set-
ting the agenda for the coming years on food, nutrition and lifestyle, and the prevention
of cancer. Current recommendations in this Expert Report, based on meta-analysis and
summaries of scientific articles, are presented in Table 2.
It is essential to understand that the evidence used to formulate the WCRF global
networks health recommendations and research policy is based on the latest research
investigation. It summarizes accumulated knowledge from about 10,000 scientific
articles.
Table 2
World Cancer Research Fund and American Institute for Cancer Research, Guidelines for
Cancer Prevention Through Diet and Physical Activity, 2007
Be as lean as possible within the normal range of body weight
Ensure that body weight through childhood and adolescent growth projects toward the
lower end of the normal BMI range at age 21
Maintain body weight within the normal range from age 21
Avoid weight gain and increases in waist circumference throughout adulthood
Be physically active as a part of everyday life
Be moderately physically active, equivalent to brisk walking, for at least 30 min every
day. As fitness improves, aim for 60 min or more of moderate, or for 30 min or more of
vigorous, physical activity every day
Limit sedentary habits such as watching television
Limit consumption of energy-dense foods and avoid sugary drinks
Consume energy-dense foods sparingly
Avoid sugary drinks
Consume “fast foods” sparingly, if at all
Eat mostly foods of plant origin
Eat at least five portions/servings (at least 400 g or 14 oz) of a variety of nonstarchy
vegetables and of fruits every day
Limit intake of red meat and avoid processed meat
(continued)
186 Wolk
Table 2
(continued)
People who eat red meat from domesticated animals (beef, pork, lamb, goat) should
consume less than 500 g (18 oz) a week, very little if any to be processed (meats
preserved by smoking, curing or salting, or addition of chemical preservatives)
Limit alcoholic drinks
If alcoholic drinks are consumed, limit consumption to no more than two drinks a day for
men and one drink a day for women
Limit consumption of salt and avoid mouldy cereals (grains) or pulses (legumes)
Avoid salt-preserved, salted or salty foods; preserve foods without using salt. Limit
consumption of processed foods with added salt to ensure an intake of less than 6 g
(2.4 g sodium) a day. Do not eat cereals (grains) or pulses (legumes) that have mold
Aim to meet nutritional needs through diet alone
Dietary supplements are not recommended for cancer prevention
Mothers should breastfeed; children should be breastfed
Aim to breastfeed infants exclusively up to 6 months and continue with complementary
feeding thereafter
Cancer survivors should follow the recommendations for cancer prevention
All cancer survivors should receive nutritional care from an appropriately trained
professional. If able to do so, and unless otherwise advised, aim to follow the
recommendations for diet, healthy weight, and physical activity
7. MEDITERRANEAN DIET AND CANCER
Interestingly, many aspects in the guidelines on nutrition for cancer prevention are
very similar to dietary food patterns usually seen in Mediterranean basin countries, such
as Greece, Italy, Spain, and France. The term “Mediterranean diet” reflects the dietary
pattern characteristics of several Mediterranean countries during the early 1960s. Such
patterns defined in the early 1990s are composed of (124):
• Abundant plant foods (vegetables, fruits, breads, other forms of cereals, beans, nuts, and seeds)
• Minimally processed, seasonally fresh, and locally grown foods
• Fresh fruits as typical daily dessert, and sweets based on nuts, olive oil, and concentrated
sugars or honey consumed on feast days
• Olive oil as the principal source of dietary fat
• Dairy products (mainly cheese and yoghurt) consumed in low to moderate amounts
• Fewer than four eggs consumed per week
• Red meat consumed in low frequency and amounts
• Wine consumed in low to moderate amounts, generally with meals
Various aspects of the Mediterranean diet are considered favorable with regards to
cancer risk. Studies have suggested that the cancer-conferring benefits of this diet are
due to not only high consumption of fruits, vegetable, whole grains, and fish but also
olive oil (125,126). The Greek variant of the Mediterranean diet is especially interesting
because Greeks have been in the area longer than other Mediterranean populations, and
the early studies that pointed to the beneficial effects of the Mediterranean diet were
Chapter 9 / Diet and Physical Activity in Cancer Prevention 187
largely based in Greece (3). The diet of Crete is considered to represent the traditional
diet of Greece prior to 1960 (127). Overall, the traditional Mediterranean diet may be
thought of as having eight components:
1. High monounsaturated/saturated fat ratio
2. Moderate ethanol consumption
3. High consumption of legumes
4. High consumption of grain products (particularly bread)
5. High consumption of fruits
6. High consumption of vegetables
7. Low consumption of meat and meat products
8. Moderate consumption of milk and dairy products
A diet that has all of the characteristics described above has a score of eight, whereas
a diet with none of these characteristics should have a score of zero. It has been reported
that death rates were lower and life expectancy was longer among people scoring high
on this dietary pattern compared with those with low scores (128,129).
In the Mediterranean diet, meals usually contain large quantities of whole-grain
bread. Legumes and vegetables are consumed in large amounts in cooked dishes, soups,
and salads are prepared with olive oil. Intake of milk is moderate, but consumption of
cheese, and to a lesser extent yoghurt, is high; feta cheese is regularly added to most
salads and vegetable stews. Meat, being expensive, used to be rarely consumed, whereas
fish consumption was a function of proximity to the sea. Wine is consumed in moderation
and almost always during meals (130). These characteristics of the Mediterranean diet
are still well reflected in the per capita availability of foods in Greece in 1990s as shown
in Fig. 8a–d. The most pronounced differences in consumed food amounts between
Greece and Sweden, USA, and Japan are observed for vegetables, fruits, and berries,
pulses, and nuts.
In summary, present American and WCRF guidelines on healthy diet for cancer
prevention are remarkably in line with the dietary profile of old Mediterranean traditions.
A diet rich in plant foods and whole grain and low in foods of animal origin, accompanied
by low to moderate alcohol consumption, should be actively promoted.
REFERENCES
1. WHO/IARC. World cancer report. Lyon: IARC Press, 2003.
2. Doll R, Peto R. The causes of cancer: quantitative estimates of avoidable risks of cancer in the United
States today. J Natl Cancer Inst 1981;66:1191–308.
3. Trichopoulou A, Lagiou P, Kuper H, et al. Cancer and Mediterranean dietary traditions. Cancer Epidemiol
Biomarkers Prev 2000;9:869–73.
4. Socialstyrelsen. http://www.socialstyrelsen.se, Prostate cancer mortality trends in Sweden, 2006.
5. WHO. Prevention of Cancer. Geneva: WHO, 1964.
6. Harvard Report on Cancer Prevention. Volume 1: Causes of human cancer. Cancer Causes Control
1996;7 Suppl 1:S3–59.
7. Colditz GA, Sellers TA, Trapido E. Epidemiology – identifying the causes and preventability of cancer?
Nat Rev Cancer 2006;6:75–83.
8. Bergstrom A, Pisani P, Tenet V, et al. Overweight as an avoidable cause of cancer in Europe. Int J Cancer
2001;91:421–30.
188 Wolk
9. Vainio H, Bianchini F. Weight control and physical activity. Lyon: IARC Press, 2002.
10. World Cancer Research Fund and American Institute for Cancer Research. Food, Nutrition and the
Prevention of Cancer: A Global Perspective. Washington, DC: World Cancer Research Fund and
American Institute for Cancer Research, 1997.
11. Lichtenstein P, Holm NV, Verkasalo PK, et al. Environmental and heritable factors in the causation of
cancer–analyses of cohorts of twins from Sweden, Denmark, and Finland. N Engl J Med 2000;343:78–85.
12. Czene K, Lichtenstein P, Hemminki K. Environmental and heritable causes of cancer among 9.6
million individuals in the Swedish family-cancer database. Int J Cancer 2002;99:260–6.
13. Boyle P, Autier P, Bartelink H, et al. European code against cancer and scientific justification: third
version (2003). Ann Oncol 2003;14:973–1005.
14. Larsson SC, Adami HO, Wolk A. Obesity, diabetes, and risk of cancer. In: Mantzoros CS, ed. Obesity
and diabetes. Totowa: Humana Press, 2006.
15. WHO. WHO Global Infobase. Geneve: WHO, 2007.
16. Orsini N, Bellocco R, Bottai M, et al. Age and temporal trends of total physical activity among Swedish
women. Med Sci Sports Exerc 2006;38:240–5.
17. Norman A, Bellocco R, Vaida F, et al. Age and temporal trends of total physical activity in Swedish
men. Med Sci Sports Exerc 2003;35:617–22.
18. Statistics, Sweden. National Health Interview Survey, 2006.
19. Time trends in smoking in the USA, 1980–2005. Atlanta, GA: Center for Disease Control and
Prevention, 2006.
20. WHO. Smoking in Greece and Japan. Geneva: WHO, 2006.
21. Hsing AW, Devesa SS. Trends and patterns of prostate cancer: what do they suggest? Epidemiol Rev
2001;23:3–13.
22. Wolk A. Diet, lifestyle and risk of prostate cancer. Acta Oncol 2005;44:277–81.
23. Rodriguez C, McCullough ML, Mondul AM, et al. Meat consumption among Black and White men
and risk of prostate cancer in the Cancer Prevention Study II Nutrition Cohort. Cancer Epidemiol
Biomarkers Prev 2006;15:211–6.
24. Chan JM, Gann PH, Giovannucci EL. Role of diet in prostate cancer development and progression.
J Clin Oncol 2005;23:8152–60.
25. Stuart GR, Holcroft J, de Boer JG, et al. Prostate mutations in rats induced by the suspected human
carcinogen 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine. Cancer Res 2000;60:266–8.
26. Cross AJ, Peters U, Kirsh VA, et al. A prospective study of meat and meat mutagens and prostate cancer
risk. Cancer Res 2005;65:11779–84.
27. Platz EA, Helzlsouer KJ. Selenium, zinc, and prostate cancer. Epidemiol Rev 2001;23:93–101.
28. Leitzmann MF, Stampfer MJ, Wu K, et al. Zinc supplement use and risk of prostate cancer. J Natl
Cancer Inst 2003;95:1004–7.
29. Larsson SC, Wolk K, Brismar K, et al. Association of diet with serum insulin-like growth factor I in
middle-aged and elderly men. Am J Clin Nutr 2005c;81:1163–7.
30. Renehan AG, Zwahlen M, Minder C, et al. Insulin-like growth factor (IGF)-I, IGF binding protein-3,
and cancer risk: systematic review and meta-regression analysis. Lancet 2004;363:1346–53.
31. Giovannucci E, Rimm EB, Wolk A, et al. Calcium and fructose intake in relation to risk of prostate
cancer. Cancer Res 1998;58:442–7.
32. Giovannucci E. Meta-analysis of coffee consumption and risk of colorectal cancer. Am J Epidemiol
1998;147:1043–52.
33. Holmes MD, Pollak MN, Willett WC, et al. Dietary correlates of plasma insulin-like growth factor I
and insulin-like growth factor binding protein 3 concentrations. Cancer Epidemiol Biomarkers Prev
2002;11:852–61.
34. Thornburg T, Turner AR, Chen YQ, et al. Phytanic acid, AMACR and prostate cancer risk. Future
Oncol 2002;2:213–23.
35. IARC. Fruit and vegetables. IARC handbooks of cancer prevention. Volume 8. Lyon: IARC Press, 2003.
36. Kristal AR, Schenk JM. Directions for future epidemiological research in lycopene and prostate cancer
risk. J Nutr 2005;135:2037S–9S.
37. Etminan M, Takkouche B, Caamano-Isorna F. The role of tomato products and lycopene in the
prevention of prostate cancer: a meta-analysis of observational studies. Cancer Epidemiol Biomarkers
Prev 2004;13:340–5.
Chapter 9 / Diet and Physical Activity in Cancer Prevention 189
38. Key TJ, Allen N, Appleby P, et al. Fruits and vegetables and prostate cancer: no association among
1104 cases in a prospective study of 130544 men in the European Prospective Investigation into Cancer
and Nutrition (EPIC). Int J Cancer 2004;109:119–24.
39. Giovannucci E, Rimm EB, Liu Y, et al. A prospective study of cruciferous vegetables and prostate
cancer. Cancer Epidemiol Biomarkers Prev 2003;12:1403–9.
40. Garikapaty VP, Ashok BT, Tadi K, et al. Synthetic dimer of indole-3-carbinol: Second generation diet
derived anti-cancer agent in hormone sensitive prostate cancer. Prostate 2006;66:453–62.
41. Hou Z, Lambert JD, Chin KV, et al. Effects of tea polyphenols on signal transduction pathways related
to cancer chemoprevention. Mutat Res 2004;555:3–19.
42. Heinonen OP, Albanes D, Virtamo J, et al. Prostate cancer and supplementation with alpha-tocopherol
and beta-carotene: incidence and mortality in a controlled trial. J Natl Cancer Inst 1998;90:440–6.
43. Shukla S, Gupta S. Dietary agents in the chemoprevention of prostate cancer. Nutr Cancer
2005;53:18–32.
44. Helzlsouer KJ, Huang HY, Alberg AJ, et al. Association between alpha-tocopherol, gamma-tocopherol,
selenium, and subsequent prostate cancer. J Natl Cancer Inst 2000;92:2018–23.
45. Li H, Stampfer MJ, Giovannucci EL, et al. A prospective study of plasma selenium levels and prostate
cancer risk. J Natl Cancer Inst 2004;96:696–703.
46. Duffield-Lillico AJ, Dalkin BL, Reid ME, et al. Selenium supplementation, baseline plasma selenium
status and incidence of prostate cancer: an analysis of the complete treatment period of the Nutritional
Prevention of Cancer Trial. BJU Int 2003;91:608–12.
47. McCann MJ, Gill CI, McGlynn H, et al. Role of mammalian lignans in the prevention and treatment of
prostate cancer. Nutr Cancer 2005;52:1–14.
48. Wikstrom P, Bylund A, Zhang JX, et al. Rye bran diet increases epithelial cell apoptosis and decreases
epithelial cell volume in TRAMP (transgenic adenocarcinoma of the mouse prostate) tumors. Nutr
Cancer 2005;53:111–6.
49. Hedelin M, Klint A, Chang ET, et al. Dietary phytoestrogen, serum enterolactone and risk of prostate
cancer: the cancer prostate sweden study (sweden). Cancer Causes Control 2006;17:169–80.
50. Terry P, Lichtenstein P, Feychting M, et al. Fatty fish consumption and risk of prostate cancer. Lancet
2001;357:1764–6.
51. Schwartz GG. Vitamin D and the epidemiology of prostate cancer. Semin Dial 2005;18:276–89.
52. Hunter DJ, Spiegelman D, Adami HO, et al. Cohort studies of fat intake and the risk of breast cancer–
a pooled analysis. N Engl J Med 1996;334:356–61.
53. Smith-Warner SA, Spiegelman D, Yaun SS, et al. Intake of fruits and vegetables and risk of breast
cancer: a pooled analysis of cohort studies. JAMA 2001;285:769–76.
54. van den Brandt PA, Spiegelman D, Yaun SS, et al. Pooled analysis of prospective cohort studies on
height, weight, and breast cancer risk. Am J Epidemiol 2000;152:514–27.
55. Linos E, Holmes MD, Willett WC. Diet and breast cancer. Curr Oncol Rep 2007;9:31–41.
56. Smith-Warner SA, Spiegelman D, Adami HO, et al. Types of dietary fat and breast cancer: a pooled
analysis of cohort studies. Int J Cancer 2001;92:767–74.
57. Smith-Warner SA, Spiegelman D, Yaun SS, et al. Alcohol and breast cancer in women: a pooled analysis
of cohort studies. JAMA 1998;279:535–40.
58. Zhang S, Hunter DJ, Hankinson SE, et al. A prospective study of folate intake and the risk of breast
cancer. JAMA 1999;281:1632–7.
59. Zhang SM, Willett WC, Selhub J, et al. Plasma folate, vitamin B6, vitamin B12, homocysteine, and risk
of breast cancer. J Natl Cancer Inst 2003;95:373–80.
60. Kim EH, Willett WC, Colditz GA, et al. Dietary fat and risk of postmenopausal breast cancer in a
20-year follow-up. Am J Epidemiol 2006;164:990–7.
61. Wolk A, Bergstrom R, Hunter D, et al. A prospective study of association of monounsaturated fat and
other types of fat with risk of breast cancer. Arch Intern Med 1998;158:41–5.
62. Voorrips LE, Brants HA, Kardinaal AF, et al. Intake of conjugated linoleic acid, fat, and other fatty
acids in relation to postmenopausal breast cancer: the Netherlands Cohort Study on Diet and Cancer.
Am J Clin Nutr 2002;76:873–82.
63. Cho E, Spiegelman D, Hunter DJ, et al. Premenopausal fat intake and risk of breast cancer. J Natl Cancer
Inst 2003;95:1079–85.
64. Holmes MD, Willett WC. Does diet affect breast cancer risk? Breast Cancer Res 2004;6:170–8.
190 Wolk
65. Mattisson I, Wirfalt E, Johansson U, et al. Intakes of plant foods, fibre and fat and risk of breast cancer–
a prospective study in the Malmo Diet and Cancer Cohort. Br J Cancer 2004;90:122–7.
66. Chen WY, Willett, WC, Rossner, GA, et al. Moderate alcohol consumption and breast cancer risk
(abstract). J Clin Oncol Proc ASCO 2005;23:515.
67. Reichman ME, Judd JT, Longcope C, et al. Effects of alcohol consumption on plasma and urinary
hormone concentrations in premenopausal women. J Natl Cancer Inst 1993;85:722–7.
68. Suzuki R, Ye W, Rylander-Rudqvist T, et al. Alcohol and postmenopausal breast cancer risk defined by
estrogen and progesterone receptor status: a prospective cohort study. J Natl Cancer Inst 2005;97:1601–8.
69. Fuchs CS, Stampfer MJ, Colditz GA, et al. Alcohol consumption and mortality among women. N Engl
J Med 1995;332:1245–50.
70. van Gils CH, Peeters PH, Bueno-de-Mesquita HB, et al. Consumption of vegetables and fruits and risk
of breast cancer. JAMA 2005;293:183–93.
71. Missmer SA, Smith-Warner SA, Spiegelman D, et al. Meat and dairy food consumption and breast
cancer: a pooled analysis of cohort studies. Int J Epidemiol 2002;31:78–85.
72. McCullough ML, Rodriguez C, Diver WR, et al. Dairy, calcium, and vitamin D intake and postmeno-
pausal breast cancer risk in the Cancer Prevention Study II Nutrition Cohort. Cancer Epidemiol Biomarkers
Prev 2005;14:2898–904.
73. John EM, Schwartz GG, Dreon DM, et al. Vitamin D and breast cancer risk: the NHANES I Epidemiologic
follow-up study, 1971–1975 to 1992. National Health and Nutrition Examination Survey. Cancer
Epidemiol Biomarkers Prev 1999;8:399–406.
74. Bertone-Johnson ER, Chen WY, Holick MF, et al. Plasma 25-hydroxyvitamin D and 1,25-dihydroxy-
vitamin D and risk of breast cancer. Cancer Epidemiol Biomarkers Prev 2005;14:1991–7.
75. Zhang S, Hunter DJ, Forman MR, et al. Dietary carotenoids and vitamins A, C, and E and risk of breast
cancer. J Natl Cancer Inst 1999;91:547–56.
76. Tamimi RM, Hankinson SE, Campos H, et al. Plasma carotenoids, retinol, and tocopherols and risk of
breast cancer. Am J Epidemiol 2005;161:153–60.
77. Parkin DM, Bray F, Ferlay J, et al. Global cancer statistics, 2002. CA Cancer J Clin 2005;55:74–108.
78. Larsson SC. Diet and gastrointestinal cancer – one-carbon metabolism and other aspects. Stockholm:
Karolinska Institutet, 2006.
79. Larsson SC, Wolk A. Meat consumption and risk of colorectal cancer: a meta-analysis of prospective
studies. Int J Cancer 2006a;119:2657–64.
80. Narisawa T, Magadia NE, Weisburger JH, et al. Promoting effect of bile acids on colon carcinogenesis
after intrarectal instillation of N-methyl-N¢-nitro-Nnitrosoguanidine in rats. J Natl Cancer Inst
1974;53:1093–7.
81. Giovannucci E, Goldin B. The role of fat, fatty acids, and total energy intake in the etiology of human
colon cancer. Am J Clin Nutr 1997;66:1564S–71S.
82. Lee DH, Anderson KE, Harnack LJ, et al. Heme iron, zinc, alcohol consumption, and colon cancer:
Iowa Women’s Health Study. J Natl Cancer Inst 2004;96:403–7.
83. Larsson SC, Adami HO, Giovannucci E, et al. Heme iron, zinc, alcohol consumption, and risk of colon
cancer. J Natl Cancer Inst 2005b;97:232–3.
84. Larsson SC. Diet and gastrointestinal cancer – one carbon metabolism and other aspects (PhD thesis)
Stockholm: Karolinska Institutet, 2006.
85. Becker W, Pearson M. Riksmaten 1997–98. Dietary habits and nutrient intake in Sweden. The second
national food consumption survey. Uppsala (Sweden): Livsmedelsverket, 2002.
86. Cotton PA, Subar AF, Friday JE, et al. Dietary sources of nutrients among US adults, 1994 to 1996.
J Am Diet Assoc 2004;104:921–30.
87. Parodi PW. Cows’ milk fat components as potential anticarcinogenic agents. J Nutr 1997;127:1055–60.
88. Molkentin J. Occurrence and biochemical characteristics of natural bioactive substances in bovine milk
lipids. Br J Nutr 2000;84 Suppl 1:S47–53.
89. Kim KH, Park HS. Dietary supplementation of conjugated linoleic acid reduces colon tumor incidence in
DMH-treated rats by increasing apoptosis with modulation of biomarkers. Nutrition 2003;19:772–7.
90. Larsson SC, Bergkvist L, Wolk A. High-fat dairy food and conjugated linoleic acid intakes in
relation to colorectal cancer incidence in the Swedish Mammography Cohort. Am J Clin Nutr 2005d;
82:894–900.
Chapter 9 / Diet and Physical Activity in Cancer Prevention 191
91. Cho E, Smith-Warner SA, Spiegelman D, et al. Dairy foods, calcium, and colorectal cancer: a pooled
analysis of 10 cohort studies. J Natl Cancer Inst 2004;96:1015–22.
92. Larsson SC, Bergkvist L, Ruteg rd J, et al. Calcium and dairy food intakes are inversely associated
with colorectal cancer risk in the Cohort of Swedish Men. Am J Clin Nutr 2006;83:667–73.
93. Newmark HL, Wargovich MJ, Bruce WR. Colon cancer and dietary fat, phosphate, and calcium: a
hypothesis. J Natl Cancer Inst 1984;72:1323–5.
94. Lamprecht SA, Lipkin M. Chemoprevention of colon cancer by calcium, vitamin D and folate: molecular
mechanisms. Nat Rev Cancer 2003;3:601–14.
95. Lipkin M. Preclinical and early human studies of calcium and colon cancer prevention. Ann N Y Acad
Sci 1999;889:120–7.
96. Baron JA, Beach M, Mandel JS, et al. Calcium supplements for the prevention of colorectal adenomas.
Calcium Polyp Prevention Study Group. N Engl J Med 1999;340:101–7.
97. Bonithon-Kopp C, Kronborg O, Giacosa A, et al. Calcium and fibre supplementation in prevention
of colorectal adenoma recurrence: a randomised intervention trial. European Cancer Prevention
Organisation Study Group. Lancet 2000;356:1300–6.
98. Riboli E, Norat T. Epidemiologic evidence of the protective effect of fruit and vegetables on cancer
risk. Am J Clin Nutr 2003;78:559S–69S.
99. Burkitt DP. Epidemiology of cancer of the colon and rectum. Cancer 1971;28:3–13.
100. Kushi LH, Meyer KA, Jacobs DR, Jr. Cereals, legumes, and chronic disease risk reduction: evidence
from epidemiologic studies. Am J Clin Nutr 1999;70:451S–8S.
101. Michels KB, Willett WC, Fuchs CS, et al. Coffee, tea, and caffeine consumption and incidence of
colon and rectal cancer. J Natl Cancer Inst 2005;97:282–92.
102. Larsson SC, Bergkvist L, Giovannucci E, et al. Coffee consumption and incidence of colorectal cancer
in two prospective cohort studies of Swedish women and men. Am J Epidemiol 2006c;163:638–44.
103. Sun CL, Yuan JM, Koh WP, et al. Green tea, black tea and colorectal cancer risk: a meta-analysis of
epidemiologic studies. Carcinogenesis 2006;27:1301–9.
104. Larsson SC, Wolk A. Epidemiology of obesity and diabetes, prevalence and trends. In: Mantzoros CS,
ed. Obesity and diabetes. Boston: Humana, 2006:15–36.
105. Nestle M. Increasing portion sizes in American diets: more calories, more obesity. J Am Diet Assoc
2003;103:39–40.
106. Calle EE, Kaaks R. Overweight, obesity and cancer: epidemiological evidence and proposed mecha-
nisms. Nat Rev Cancer 2004;4:579–91.
107. Calle EE, Rodriguez C, Walker-Thurmond K, et al. Overweight, obesity, and mortality from cancer in
a prospectively studied cohort of U.S. adults. N Engl J Med 2003;348:1625–38.
108. Monninkhof EM, Elias SG, Vlems FA, et al. Physical activity and breast cancer: a systematic review.
Epidemiology 2007;18:137–57.
109. Dallal C, Sullivan-Halley J, Ross R. Long-term recreational physical activity and risk of invasive and
in situ breast cancer. Arch Intern Med 2007;167:408–15.
110. Friberg E, Mantzoros CS, Wolk A. Physical activity and risk of endometrial cancer: a population-
based prospective cohort study. Cancer Epidemiol Biomarkers Prev 2006;15:2136–40.
111. Friberg E, Mantzoros CS, Wolk A. Diabetes and risk of endometrial cancer: a population-based pro-
spective cohort study. Cancer Epidemiol Biomarkers Prev 2007;16:276–80.
112. Irwin ML, Yasui Y, Ulrich CM, et al. Effect of exercise on total and intra-abdominal body fat in post-
menopausal women: a randomized controlled trial. JAMA 2003;289:323–30.
113. McTiernan A, Tworoger SS, Rajan KB, et al. Effect of exercise on serum androgens in postmenopausal
women: a 12-month randomized clinical trial. Cancer Epidemiol Biomarkers Prev 2004;13:1099–105.
114. Goodyear LJ, Kahn BB. Exercise, glucose transport, and insulin sensitivity. Annu Rev Med
1998;49:235–61.
115. Gapstur SM, Kopp P, Chiu BC, et al. Longitudinal associations of age, anthropometric and lifestyle
factors with serum total insulin-like growth factor-I and IGF binding protein-3 levels in Black and
White men: the CARDIA Male Hormone Study. Cancer Epidemiol Biomarkers Prev 2004;13:2208–16.
116. Ring-Dimitriou S, Paulweber B, von Duvillard SP, et al. The effect of physical activity and physical
fitness on plasma adiponectin in adults with predisposition to metabolic syndrome. Eur J Appl Physiol
2006;98:472–81.
192 Wolk
117. Mantzoros C, Petridou E, Dessypris N, et al. Adiponectin and breast cancer risk. J Clin Endocrinol
Metab 2004;89:1102–7.
118. Petridou E, Mantzoros C, Dessypris N, et al. Plasma adiponectin concentrations in relation to endo-
metrial cancer: a case-control study in Greece. J Clin Endocrinol Metab 2003;88:993–7.
119. Samad AK, Taylor RS, Marshall T, et al. A meta-analysis of the association of physical activity with
reduced risk of colorectal cancer. Colorectal Dis 2005;7:204–13.
120. Lichtenstein AH, Appel LJ, Brands M, et al. Summary of American Heart Association Diet and Life-
style Recommendations revision 2006. Arterioscler Thromb Vasc Biol 2006;26:2186–91.
121. American Diabetes Association. ADA Dietary Guidelines. Alexandria, VA: ADA, 2006.
122. US Department of Health and Human Services and US Department of Agriculture. Dietary guidelines
for Americans. Washington, DC: US Government Printing Office, US Department of Health and
Human Services, US Department of Agriculture, 2005.
123. Kushi LH, Byers T, Doyle C, et al. American Cancer Society Guidelines on Nutrition and Physical
Activity for cancer prevention: reducing the risk of cancer with healthy food choices and physical
activity. CA Cancer J Clin 2006;56:254–81; quiz 313–4.
124. Serra-Majem L, Roman B, Estruch R. Scientific evidence of interventions using the Mediterranean
diet: a systematic review. Nutr Rev 2006;64:S27–47.
125. Owen RW, Haubner R, Wurtele G, et al. Olives and olive oil in cancer prevention. Eur J Cancer Prev
2004;13:319–26.
126. Colomer R, Menendez JA. Mediterranean diet, olive oil and cancer. Clin Transl Oncol 2006;8:15–21.
127. Simopoulos AP. The traditional diet of Greece and cancer. Eur J Cancer Prev 2004;13:219–30.
128. Trichopoulou A. Traditional Mediterranean diet and longevity in the elderly: a review. Public Health
Nutr 2004;7:943–7.
129. Trichopoulou A, Costacou T, Bamia C, et al. Adherence to a Mediterranean diet and survival in a
Greek population. N Engl J Med 2003;348:2599–608.
130. Helsing E, Trichopoulou A. The Mediterranean diet and food culture: a symposium. Eur J Clin Nutr
1989;43:1–92.
10 Food Guide Pyramids and the 2005
MyPyramid
Jessica Fargnoli and Christos S. Mantzoros
KEY POINTS
• In 1992, the USDA introduced the Food Guide Pyramid as a simple tool to aid the public
in selecting and preparing the best foods for overall health and for prevention of chronic
disease.
• The scientific community has been divided over the effectiveness and accuracy of the
information relayed by the food pyramid.
• In response to evolving scientific concepts and evidence, the USDA released an updated Food
Guide Pyramid, called MyPyramid, in 2005.
• The recommendations in the revised Food Pyramid and Dietary Guidelines are based on
currently available scientific evidence, but some still doubt whether the new Pyramid includes
enough valuable information to truly guide the public to a healthier lifestyle.
Key Words: USDA Food Pyramids, Nutrition recommendations
1. HISTORY OF THE DIETARY GUIDELINES
AND THE FOOD PYRAMIDS
Since 1894, the United States Department of Agriculture (USDA) has been providing
the public with food guidance based on scientific evidence of food’s nutritional value.
WO Atwater paved the way for the first USDA food guides with his research compiling
food composition tables and determining nutritional requirements for the US population
(1). The USDA released the first official food guide in 1916. Developed by Caroline
Hunt, a nutrition specialist at the USDA, the guide placed food into five groups: milk
and meat, cereals, vegetables and fruits, fats and fat foods, and sugars and sugary foods
(2). Over time, food guides have been updated and revised as knowledge has changed,
but the idea of selecting a variety of foods from different nutritional groups has been
consistent since people usually eat a variety of foods. Among the most popular food
guides was the “Basic Four.” Released in 1956, this guide divided food into four categories:
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_10,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
195
196 Fargnoli and Mantzoros
dairy, meat, grains, and fruit and vegetables. In 1979, a fifth group was added for fats,
sweets, and alcohol (2), and this is generally how food has been characterized by the
USDA since then.
In response to the public’s need for more comprehensive nutrition information, the
USDA and DHHS released the first Dietary Guidelines for Americans booklet in1980.
Developed to help individuals to choose and prepare foods for optimum health and
prevention of chronic disease, this new food guide offered more detailed information
about how to select the most nutritious foods and the harm caused by the least nutritious,
along with recommendations on how to maintain a healthy body weight (3). The first
Dietary Guidelines encouraged consumption of a variety of foods, including starch and
fiber, along with avoidance of fats, sugars, and sodium. It also recommended moderation
of alcoholic beverages.
After implementation of the new dietary guidelines, it was found that consumers and
some professionals were largely unaware of its existence. Many thought that the USDA
was still using the “Basic Four” (4). To remedy this, the USDA began research and
development of a visual representation of the Dietary Guidelines in 1988. When designing
the graph, the USDA stressed that it must convey variety, proportionality, moderation, and
usability (4). Many potential designs, such as shopping carts, circles, and funnel shapes,
were tested for their ability to express these ideas. The pyramid and a bowl shape were
most successful, but the pyramid was chosen for its edge in communicating the ideas of
proportionality and moderation (4). The resulting Food Guide Pyramid promoted a diet
based heavily on bread, cereal, rice, and pasta (6–11 servings a day) and very low in fats
and refined sugars (5). It also recommended liberal consumption of fruits and vegetables,
and two–three servings of meat and dairy a day. By this time, the differences between
harmful saturated fats and beneficial unsaturated fats were well known. Despite this, the
government largely considered the American public unable to distinguish between
different types of fat (6). Therefore, the Dietary Guidelines and corresponding Food
Guide Pyramid offered no distinction between types of fat and promoted an overall
low-fat diet in order to reduce consumption of saturated fats (6) (Fig. 1).
The release of the first Food Guide Pyramid was met with both support and criticism.
For most, the largest inadequacy of the first Food Guide Pyramid was its simplicity. To
many, it did not offer enough information to select the most nutritious foods within each
food group. Some nutritional experts criticized its failure to distinguish between harmful
animal fats and beneficial vegetable oils (6–8), especially in light of the fact that the
food guides of several nations, such as China, Australia, and Greece, address the use
of different types of fat (6). Others worried that the public would be confused because
the Food Guide Pyramid did not make a distinction between red meat and other apparently
healthier foods, such as poultry, fish, legumes, and eggs in the protein group (8). The
pyramid put an emphasis on consumption of breads, cereal products, and potatoes,
though there was no evidence of a clear benefit from this (8). Some thought it should
be more specific about the consumption of whole grains leading to a decreased risk in
heart disease rather than lumping all grains together in one recommendation (8). The
Pyramid was also criticized for lacking valuable information on physical activity and
sodium and alcohol intake along with recommending confusing serving sizes that could
lead to excess calorie consumption (6). Perhaps the only recommendation of the Food
Guide Pyramid not to be disputed was increased consumption of fruit and vegetables.
Chapter 10 / Food Guide Pyramids and the 2005 MyPyramid 197
Fats, Oils & Sweets KEY
USE SPARINGLY Fat (naturally occuring and added)
Sugars (added)
These symbols show fats and added sugars in foods.
Milk, Yogurt & Meat, Poultry, Fish, Dry Beans,
Cheese Group Eggs & Nuts Group
2-3 SERVINGS 2-3 SERVINGS
Vegetable Group Fruit Group
3-5 SERVINGS 2-4 SERVINGS
Bread, Cereal,
Rice & Pasta
Group
6-11
SERVINGS
Fig. 1. 1992 USDA Food Guide Pyramid.
Those who came to the Pyramid’s defense proposed that its core recommendations of
variety, proportionality, and moderation are valid and that the obesity epidemic is a result
of the public’s failure to follow these suggestions (9). Despite the criticism, over a decade
elapsed before the USDA released a revised version of the Food Guide Pyramid.
2. THE 2005 MYPYRAMID
In response to both widespread criticism and changing nutritional knowledge, the
USDA released an updated version of the Food Guide Pyramid in 2005. As part of
the revision it was renamed MyPyramid, to promote individuality in food choices,
and was modernized with a companion website, http://www.mypyramid.gov. The new
image itself contains very little information about each food group and no daily intake
suggestions. It is intentionally vague, broadly representing the food groups and the
recommendations of activity, moderation, personalization, proportionality, variety, and
gradual improvement. The food groups are also now represented as vertical rather than
horizontal bands on the pyramid. MyPyramid relies heavily on the website, MyPyramid.
gov, and descriptive handouts to disseminate more detailed information about selecting
foods and what quantities to eat. “Inside the Pyramid,” on MyPyramid.gov, contains
detailed explanations about each group of foods and offers information on how to choose
the most healthful foods (Fig. 2).
In the information online, the 2005 Pyramid differentiates between different foods in
the grain group, recommending that at least half of the public’s grain intake should be
from whole grains. Like the earlier version, this new pyramid also encourages a low-fat
diet, but advises the public to choose healthier vegetable oils over solid animal fats.
198 Fargnoli and Mantzoros
Fig. 2. 2005 MyPyramid (adapted from www.mypyramid.gov).
The 2005 Pyramid also offers more detailed recommendations in the meats and beans
group, advocating for lean or low-fat meat choices and suggesting that fish, nuts, and
seeds should be chosen over meat when possible. The revised Food Pyramid also improves
upon its lack of information on physical activity and its previously confusing serving
sizes. Exercise is now represented on the Pyramid and it recommends at least 30 min
of physical activity a day. No longer does the Pyramid offer serving size suggestions
for each group, instead the MyPyramid Plan on the MyPyramid.gov website calculates
individualized serving needs based on gender, weight, age, and physical activity.
Another feature of MyPyramid.gov is the MyPyramidTracker. This online tool
assesses the user’s dietary and physical activity and calculates his or her energy balance.
It allows each individual to track their own adherence to the Food Pyramid guidelines
and adjust their intake accordingly.
Although the new, interactive Pyramid has addressed many of the problems of its
predecessor, it has still been the subject of some criticism. MyPyramid.gov offers a
wealth of educational materials, but it is not readily available to underprivileged
populations who are at high risk for many chronic diseases (10). Further research on
the new Food Guide Pyramid should be conducted to determine if its recommendations
are truly reaching the American public.
The USDA’s Food Guide Pyramid has undergone tremendous revision and now offers
much more detailed recommendations, which are very similar to those of other nations,
such as Japan and Canada (11). In the wake of the current obesity epidemic, it is essential
that the American public stay informed and educated on which foods to choose, which
to avoid, and what quantities they should eat. A graphic guide, such as the Food Guide
Chapter 10 / Food Guide Pyramids and the 2005 MyPyramid 199
Pyramid, makes this information much more accessible. In addition, the features now
offered on the corresponding MyPyramid.gov website should give users all of the tools
needed to follow the USDA’s Dietary Guidelines. The question that remains is whether
the 2005 Food Guide Pyramid truly recommends the most effective diet for preventing
chronic disease.
3. SCIENTIFIC EVIDENCE UNDERLYING THE CREATION
OF MYPYRAMID
3.1. Ecological Studies
International comparisons have helped to shed light upon the effectiveness of various
Food Pyramid recommendations in preventing chronic disease. Several studies comparing
mortality and morbidity from coronary heart disease (CHD) among different countries
have helped to elucidate the dietary factors involved. CHD mortality fell in USA and
Australia in the 1960s, though it remained constant in England and Wales, which are
comparable in demographics and quality of medical care (12). This drop in mortality
was ultimately attributed to differences in fat consumption. Citizens of USA and
Australia mostly switched from butter to margarine around 1960, and thus increased
consumption of vegetable fat, while England and Wales did not begin the switch to
margarine until 1973–1974 (12). In another study, a decline in mortality from heart
disease in Poland in the 1990s was also related to a switch from animal to plant fats,
along with increased fresh fruit and vegetable consumption (13). These findings, not-
withstanding acknowledged limitations of ecological studies, support the beneficial
nature of unsaturated plant fats over saturated animal fats.
In the Seven Countries Study, associations were found between the diets of certain
regions and CHD. The two regions with diets lowest in saturated fat intake, Japan and
the island of Crete in Greece, had the lowest mortality from ischemic heart disease.
Concurrently, Finland had both the highest saturated fat intake and highest mortality
from ischemic heart disease (14). Although the diets of the Japanese and Greeks in the
study were both characterized by low saturated fat intake, the total fat intake of Greeks
was over four times than that of the Japanese, mainly due to high consumption of olive
oil (14). These findings led to many more investigations into the benefits of choosing
vegetable oils over animal fats to prevent CHD.
Ecological studies have found several links between diet and various types of cancer
too. Research comparing cancer incidence rates internationally found olive oil consumption
to have a negative association with the development of colorectal cancer (15). Several
studies have found a connection between high intake of dietary fat (particularly animal
fat) and certain cancers, as well as an inverse association between fruit and vegetable
intake and cancer risk (16–19). Importantly, many of the associations between diet and
cancer risk seen in ecological studies have been found to be weak or nonexistent when
analyzed in prospective cohort studies or clinical trials, underlying the main drawback
of ecological studies, that is uncontrolled confounding.
3.2. Case-Control Studies
Many of the associations between dietary factors and chronic disease risk seen in
ecological studies have also been validated by case-control studies. High-fat intake has
200 Fargnoli and Mantzoros
been linked to various types of cancer, such as prostate, breast, and endometrial cancer
(20–22), along with higher risk of cardiovascular disease (CVD) (23). Patients with
severe nonalcoholic fatty liver disease (a condition related to the metabolic syndrome)
had higher saturated fatty acid intakes (14% of daily energy) than age and BMI-matched
controls (10% of daily energy) (24).
In accordance with findings from previous ecological studies, a study based in Greece
found that individuals with a closer adherence to Mediterranean diet were at decreased
risk for acute CVD (25). Higher consumption of vegetables has been connected to
decreased risk of CVD (23), and in several case-control studies, high fruit and vegetable
intake has been linked to decreased risk of pancreatic, lung, breast, ovarian, and rectal
cancer (26–32). Risk for breast cancer and other cancers has been negatively associated
with foods lower on the glycemic index, such as whole grains (33). Research on the
correlation between dairy and meat intake and various cancers has been inconclusive,
showing positive and negative association with cancer risk depending on the type. With
the possible exception of the dairy recommendations, the USDA’s dietary guidelines
seem to be consistent with most of these case-control studies.
3.3. Cohort Studies
Findings from cohort studies suggest that there is at least some relationship between
adherence to the 1992 and 2005 Food Pyramid recommendations and reduced risk of
chronic disease. Criticisms of the 1992 Food Guide Pyramid included whether it encouraged
reasonable energy intake. A study of 4,994 men and women from the Third National
Health and Nutrition Examination Survey found that participants who closely followed
the 2005 Food Guide Pyramid consumed less calories than those who closely followed
the1992 Food Guide Pyramid guidelines (34). Nutrient intakes were also improved for
those who adhered to the 2005 Pyramid, with the exception of potassium and vitamin E.
This information suggests that the 2005 Pyramid is improved in comparison to its earlier
version in meeting nutritional needs while still constraining calories.
In 1995, the Healthy Eating Index (HEI) was designed to measure adherence to
USDA’s Dietary Guidelines, with higher scores corresponding to higher observance of
the guidelines’ recommendations (35). This allowed researchers to begin assessing the
effectiveness of the dietary guidelines in preventing chronic disease. Women among a
cohort of the Nurses’ Health study whose HEI scores adhered closely to the Dietary
Guidelines were not found to be at significantly lower risk for overall chronic disease
after a 12-year follow-up period (36). They did, however, exhibit a small reduction in
CVD risk. These findings were comparable with those from a cohort of men from the
Health Professionals Follow-up Study, which found a weak inverse association between
adherence to the Dietary Guidelines and overall risk for chronic disease (37). Those
men with the highest HEI score had a 28% lower risk of CVD, but no association was
reported between HEI and cancer.
On the basis of these results, a new dietary index was developed called the Alternate
Healthy Eating Index (AHEI), which was found it to be a more reliable predictor of
chronic disease risk (38). The predicted risk of CVD and overall chronic disease was
lower for men and women with the highest AHEI scores. There was a much stronger
inverse association between CVD and adherence to the Dietary Guidelines when using
the AHEI (38).
Chapter 10 / Food Guide Pyramids and the 2005 MyPyramid 201
To examine the relationship between adherence to the 2005 Dietary Guidelines
and insulin resistance, a study was conducted in the Framingham Offspring Cohort
measuring the association between fasting insulin resistance and a diet consistent with
the 2005 Dietary Guidelines. There was a positive association between women with a
close adherence to the 2005 Dietary Guidelines and insulin sensitivity; however, no such
association was found among men (39). In prospective cohort studies, foods that are
lower on the glycemic index improve insulin sensitivity and other risk factors for CVD
(40–42). The 2005 Pyramid currently recommends making half of all grains consumed
whole grains, which are lower on the glycemic index. This may account for the increased
insulin sensitivity seen in individuals who adhere to the 2005 Dietary Guidelines.
Little relationship has been found between following the Food Pyramid and cancer
risk. Instead, some recent cohort studies have investigated the relationship between
adherence to certain food groups and risk of cancer. Among prospective cohort studies,
results are mixed on the relationship between consumption of dairy and certain cancers.
An analysis of ten cohort studies found an association between high-milk and -calcium
intake and reduced colorectal cancer risk (43). Another prospective study among the
Health Professionals Follow-up cohort found high-calcium intake to be associated with
higher risk of advanced prostate cancer (44). Further analyses of cohort studies found
no association either way between breast and ovarian cancer and dairy intake (45, 46).
Thus, on the basis of current research, there seems to be little reason for the USDA to
change their recommendations for three dairy servings per day until controlled trials are
performed. Although ecological and case-control studies pointed to fruits and vegetables
as important for cancer prevention, prospective cohort studies have shown little to no
association between fruit and vegetable intake and cancer risk (47–51). Although the
latter study design offers the time sequence criterion for causality, neither one of these
studies can prove causality. Thus, in order to truly determine the effectiveness of the
Food Guide Pyramid and its corresponding food groups at reducing the risk of chronic
disease, randomized trials must be performed.
3.4. Clinical Trials
The randomized trial is the only study design that can build on knowledge obtained
and hypotheses generated by observational studies while at the same time is not plagued
by the drawbacks of epidemiological studies. Few clinical trials to determine the Food
Guide Pyramid’s effectiveness at preventing chronic disease have been completed. One
trial conducted among active-duty Air Force members in a 90-day fitness program found
that a group receiving individualized counseling using the Food Guide Pyramid had
significant reductions in cardiovascular risk factors and an improved response to exercise
training (52). Those using the Food Guide Pyramid experienced reduced energy from fat
intake, BMI, total cholesterol levels, and LDL levels (52).
There is little information deriving from clinical trials specifically on the Food Guide
Pyramid’s effectiveness in reducing chronic disease. In addition, several other diets
have been shown to be beneficial, especially in reducing CVD outcomes, and may thus
inform future dietary recommendations. A meta-analysis of 27 clinical trials suggests
that replacing saturated fats with polyunsaturated fats is more beneficial than replacing
them with either carbohydrates or monounsaturated fats (53). In one trial, patients with
a recent acute myocardial infarction (MI) were instructed to eat a low-fat diet, and an
202 Fargnoli and Mantzoros
intervention group was also advised to eat more fruits, vegetables, nuts, and grain products.
The early initiation of the intervention (within 72 h of MI) resulted in a significant
decrease in cardiac events for the intervention group after a 1-year follow-up (54).
The group eating a diet high in fiber, vitamins, and minerals also resulted in significant
decreases in blood lipoprotein levels and fasting blood glucose.
Another trial found that mortality was reduced by about 29% in a 2-year follow-up
of patients recovering from an MI who increased their intake of fatty fish and fish oil
(55). In this same study, however, there was no evidence of benefit from increased fiber
or decreased fat. Randomized trials have also shown that a diet high in monounsaturated
fatty acids, such as those found in nuts, is more favorable than a low-fat diet, since it
lowers LDL cholesterol but not HDL cholesterol (56, 57). Diets that replace saturated
fatty acids with polyunsaturated fatty acids can reduce LDL cholesterol by 9.8% (58).
4. MEDITERRANEAN-TYPE DIET PYRAMID
Improved health outcomes have historically been associated with the diet followed
by the Mediterranean region of the world. This diet pattern is generally defined by large
intakes of whole grains and plant foods, olive oil as the major fat, low-to-moderate
intakes of dairy, fish, and poultry, low intake of red meat, and low-to-moderate con-
sumption of wine (59). The Lyon Diet Heart Study performed a randomized trial to
elucidate whether a Mediterranean-type diet might reduce the occurrence of cardiovas-
cular outcomes in patients who have had an MI. After a 4-year follow-up, the final report
confirmed the protective effects of the Mediterranean diet (60). This diet may also be
beneficial in prevention of the metabolic syndrome which is associated with type 2 diabetes
and CVD (61). Patients with the metabolic syndrome following a Mediterranean-style
diet for 2 years benefited from a reduction in inflammatory markers, decreased insulin
resistance, and improved endothelial function (61). In addition, a Mediterranean-style
diet has been shown to be associated with higher adherence rates than low-fat diets of
the same calorie intake, resulting in healthier body weight (62).
The benefits of the Mediterranean-type diet may be related to inclusion of whole grains
over refined carbohydrates, moderate alcohol intake, as well as prudent use of nuts,
especially walnuts. Several randomized trials have proven the benefits of whole grains in
decreasing risk of heart disease, such as improving insulin sensitivity and lowering LDL
cholesterol concentrations (42). Moderate alcohol consumption has also been shown to
improve insulin sensitivity, lower blood pressure, and reduce the risk of CVD, such as
ischemic stroke (63–66). A daily serving of 30 g of walnuts, which have higher polyun-
saturated fat content than other nuts, increased HDL to total cholesterol ratio in patients
with type 2 diabetes (67). In addition, walnuts have been shown to improve endothelial
function (67, 68). We have recently shown that the combination of these food items in
the context of the Mediterranean diet increases the circulating levels of adiponectin, an
adipocyte secreted hormone which acts as an endogenous insulin sensitizer. Adiponectin
can in turn improve insulin resistance, optimize glycemic control, and decrease lipid
levels and inflammatory markers.
Clinical trials hoping to determine the effects of diet on cancer risk have been less
conclusive. In the Women’s Healthy Eating and Living randomized trial among women
previously treated for breast cancer, an intervention group eating a diet low in fat and
Chapter 10 / Food Guide Pyramids and the 2005 MyPyramid 203
very high in vegetables, fruits, and fiber did not have a reduction in breast cancer events
or mortality in a 7.3-year follow-up period (69). Many of the dietary factors associated
with cancer in case-control and observational ecological studies have not been replicated
in controlled trials, making it difficult to make nutritional recommendations solely on the
basis of cancer prevention. Obesity is a risk factor for many types of cancer, however,
so diets effective in obesity prevention should be followed.
5. CONCLUSIONS
On the basis of current scientific evidence, the nutritional guidelines put forth by the
USDA are reasonable for most healthy Americans. Several prospective cohort studies
and one controlled trial have shown that closer adherence to the dietary guidelines pro-
vides at least some benefit in preventing chronic disease. However, more specificity is
necessary so that the public may truly choose the healthiest foods from each food group.
Importantly, more clinical trials are needed to conclusively demonstrate the efficacy and
cost-effectiveness of not only the guidelines in general but also the individual recom-
mendations more specifically.
Certain areas of uncertainty and/or areas where the recommendations of MyPyramid
can be improved remain. MyPyramid’s recommendation to make “half your grains whole”
has been proposed to be a step in the right direction. On the basis of overwhelming
scientific evidence on the benefits of choosing whole grains over refined carbohydrates
in preventing type 2 diabetes and CVD and the readily available array of whole grain
products now offered, it seems reasonable to recommend that Americans make all of
their grains whole whenever possible for the optimum prevention of heart disease.
High fruit and vegetable intake does not seem to have the preventative powers for
cancer that researchers once thought. Diets rich in fruits and vegetables still appear to
be beneficial for the prevention of CVD and further investigations must be performed to
determine which diets are most beneficial for cancer prevention. Fruits and vegetables
are still a source of many essential vitamins and nutrients for overall health, however,
and when added to a diet that previously lacked them, fruits and vegetables will likely
take the place of other less nutritious foods. Further clinical trials are needed to fully
substantiate these recommendations, though.
Although some associations have been made in cohort studies between dairy products
and cancer risk, the relationship is still largely inconclusive. Given currently available
evidence in conjunction with the beneficial effect of low-fat dairy products in obesity
and metabolism, there seems to be no fault in recommending low-fat and fat-free dairy
products at this time. Thus, future clinical trials must determine whether people at risk
for certain cancers should be advised to lower dairy consumption, and controlled trials
should be performed to determine what the effect of dairy products is on cancer outcomes
as well as obesity, diabetes, and the metabolic syndrome.
Several authors have suggested that MyPyramid should be more authoritative in
its advice on protein. Clinical evidence touts the benefits of fatty fish and nuts in the
prevention of CVD, type 2 diabetes, and the metabolic syndrome. Since nuts, such as
walnuts, are so useful in improving blood cholesterol profiles, it has been suggested
that the USDA should recommend that one serving of protein a day be from nuts, and
specifically walnuts, but again more clinical trials are also needed in this area. In a
204 Fargnoli and Mantzoros
healthy diet, it is believed that red meat should be eaten very sparingly, and replaced by
lean poultry and fish, as is done in the Mediterranean-type diet. In this area, it has been
suggested that the Food Pyramid does not provide enough information to guide the
public to the healthiest possible diet.
Clinical trials have consistently shown that a low-fat diet may not be as beneficial as
a diet that replaces saturated fatty acids with mono- and polyunsaturated fatty acids. For
example, the success of the Mediterranean diet in improving cardiovascular outcomes
has been largely attributed to replacing animal fats with olive oil. In addition, diets,
such as the Mediterranean, that replace saturated fats with these healthier fats are more
palatable than low-fat diets and have higher adherence rates, resulting in more sustained
weight loss and health benefits. After over a decade of advising Americans to avoid fat,
several experts believe that the USDA needs to provide more information to change
the public perception of fat (6, 7). More detailed information, and thus more detailed
clinical studies on the benefits of replacing animal fats and saturated fats with olive oil,
monounsaturated fats, and polyunsaturated fats are clearly needed.
Last but not least, in a nation where over half of adults are overweight or obese, there is
no question that authoritative dietary recommendations are necessary to educate Americans
on the healthiest food choices. The USDA’s dietary guidelines and corresponding Food
Pyramids are useful in this regard, but several experts agree that these must be more
discriminating in their advice on total energy intakes, grains, proteins, and fats based
on current scientific evidence. Alternative pyramids have been proposed, such as Walter
Willett’s Healthy Eating Pyramid, that separate refined carbohydrates from whole grains
and red meat and animal fats from leaner, more nutritious proteins.
Finally, another criticism by many experts is that the USDA’s decision to put the more
detailed information on each food group online fails to recognize the significant portion
of the US population without home internet access. Without the additional information
provided online, the 2005 pyramid is nothing more than a triangle that lists the different
food groups, leaving no way for users to choose the healthiest foods in each group.
A more effective way of distributing this information must be considered so that a large
percentage of Americans, especially the underprivileged ones who tend to be more prone
to consume a less healthy diet, are not left in the dark on the finer points of the USDA’s
nutritional guidelines.
In summary, although the 2005 MyPyramid appears to be a welcome advance in
relation to previously available guidelines, much more is needed in terms of research to
support dietary recommendations as well as public health efforts to best disseminate the
message on a diet that can prevent and/or improve adverse health outcomes.
REFERENCES
1. Welsh S. Atwater to the present: evolution of nutrition education. J Nutr 1994; 124(9 Suppl):1799S–1807S.
2. Welsh S, Davis C, Shaw A. A brief history of Food Guides in the United States. Nutrition Today 1992; 6–11.
3. U.S. Department of Agriculture and U.S. Department of Health and Human Services. Nutrition and Your
Health: Dietary Guidelines for Americans. 1980. Washington, DC, Home and Garden Bulletin.
4. Welsh S, Davis C, Shaw A. Development of the Food Guide Pyramid. Nutrition Today 1992; 12–23.
5. U.S. Department of Agriculture. The food guide pyramid. 1992. Washington, DC, Home and Garden Bulletin.
6. Gifford KD. Dietary fats, eating guides, and public policy: history, critique, and recommendations.
Am J Med 2002; 113(Suppl 9B):89S–106S.
Chapter 10 / Food Guide Pyramids and the 2005 MyPyramid 205
7. Willett WC. The dietary pyramid: does the foundation need repair. Am J Clin Nutr 1998; 68(2):218–219.
8. Willett WC, Stampfer MJ. Rebuilding the food pyramid. Sci Am 2003; 288(1):64–71.
9. Goldberg JP, Belury MA, Elam P et al. The obesity crisis: don’t blame it on the pyramid. J Am Diet
Assoc 2004; 104(7):1141–1147.
10. Johnston CS. Uncle Sam’s diet sensation: MyPyramid – an overview and commentary. MedGenMed
2005; 7(3):78.
11. Murphy SP, Barr SI. Food guides reflect similarities and differences in dietary guidance in three countries
(Japan, Canada, and the United States). Nutr Rev 2007; 65(4):141–148.
12. Hetzel BS, Charnock JS, Dwyer T, McLennan PL. Fall in coronary heart disease mortality in U.S.A.
and Australia due to sudden death: evidence for the role of polyunsaturated fat. J Clin Epidemiol 1989;
42(9):885–893.
13. Zatonski WA, McMichael AJ, Powles JW. Ecological study of reasons for sharp decline in mortality
from ischaemic heart disease in Poland since 1991. BMJ 1998; 316(7137):1047–1051.
14. Keys A. Coronary heart disease in seven countries. 1970. Nutrition 1997; 13(3):250–252.
15. Stoneham M, Goldacre M, Seagroatt V, Gill L. Olive oil, diet and colorectal cancer: an ecological study
and a hypothesis. J Epidemiol Community Health 2000; 54(10):756–760.
16. Farchi S, Saba A, Turrini A, Forlani F, Pettinelli A, D’Amicis A. An ecological study of the correlation
between diet and tumour mortality rates in Italy. Eur J Cancer Prev 1996; 5(2):113–120.
17. Sasaki S, Horacsek M, Kesteloot H. An ecological study of the relationship between dietary fat intake
and breast cancer mortality. Prev Med 1993; 22(2):187–202.
18. Kneller RW, Guo WD, Hsing AW et al. Risk factors for stomach cancer in sixty-five Chinese counties.
Cancer Epidemiol Biomarkers Prev 1992; 1(2):113–118.
19. Koo LC, Mang OW, Ho JH. An ecological study of trends in cancer incidence and dietary changes in
Hong Kong. Nutr Cancer 1997; 28(3):289–301.
20. Kristal AR, Cohen JH, Qu P, Stanford JL. Associations of energy, fat, calcium, and vitamin D with
prostate cancer risk. Cancer Epidemiol Biomarkers Prev 2002; 11(8):719–725.
21. Alothaimeen A, Ezzat A, Mohamed G, Muammar T, Al-Madouj A. Dietary fat and breast cancer in
Saudi Arabia: a case-control study. East Mediterr Health J 2004; 10(6):879–886.
22. Dalvi TB, Canchola AJ, Horn-Ross PL. Dietary patterns, Mediterranean diet, and endometrial cancer
risk. Cancer Causes Control 2007.
23. Zyriax BC, Boeing H, Windler E. Nutrition is a powerful independent risk factor for coronary heart
disease in women – the CORA study: a population-based case-control study. Eur J Clin Nutr 2005;
59(10):1201–1207.
24. Musso G, Gambino R, De MF et al. Dietary habits and their relations to insulin resistance and postprandial
lipemia in nonalcoholic steatohepatitis. Hepatology 2003; 37(4):909–916.
25. Panagiotakos DB, Pitsavos C, Matalas AL, Chrysohoou C, Stefanadis C. Geographical influences on
the association between adherence to the Mediterranean diet and the prevalence of acute coronary
syndromes, in Greece: the CARDIO2000 study. Int J Cardiol 2005; 100(1):135–142.
26. Chan JM, Wang F, Holly EA. Vegetable and fruit intake and pancreatic cancer in a population-based
case-control study in the San Francisco bay area. Cancer Epidemiol Biomarkers Prev 2005; 14(9):2093–2097.
27. Galeone C, Negri E, Pelucchi C, La VC, Bosetti C, Hu J. Dietary intake of fruit and vegetable and lung
cancer risk: a case-control study in Harbin, northeast China. Ann Oncol 2007; 18(2):388–392.
28. Malin AS, Qi D, Shu XO et al. Intake of fruits, vegetables and selected micronutrients in relation to the
risk of breast cancer. Int J Cancer 2003; 105(3):413–418.
29. Pan SY, Ugnat AM, Mao Y, Wen SW, Johnson KC. A case-control study of diet and the risk of ovarian
cancer. Cancer Epidemiol Biomarkers Prev 2004; 13(9):1521–1527.
30. Rylander R, Axelsson G. Lung cancer risks in relation to vegetable and fruit consumption and smoking.
Int J Cancer 2006; 118(3):739–743.
31. Shannon J, Ray R, Wu C et al. Food and botanical groupings and risk of breast cancer: a case-control
study in Shanghai, China. Cancer Epidemiol Biomarkers Prev 2005; 14(1):81–90.
32. Slattery ML, Curtin KP, Edwards SL, Schaffer DM. Plant foods, fiber, and rectal cancer. Am J Clin Nutr
2004; 79(2):274–281.
33. Augustin LS, Dal ML, La VC et al. Dietary glycemic index and glycemic load, and breast cancer risk:
a case-control study. Ann Oncol 2001; 12(11):1533–1538.
206 Fargnoli and Mantzoros
34. Gao X, Wilde PE, Lichtenstein AH, Tucker KL. The 2005 USDA Food Guide Pyramid is associated
with more adequate nutrient intakes within energy constraints than the 1992 Pyramid. J Nutr 2006;
136(5):1341–1346.
35. Kennedy ET, Ohls J, Carlson S, Fleming K. The Healthy Eating Index: design and applications. J Am
Diet Assoc 1995; 95(10):1103–1108.
36. McCullough ML, Feskanich D, Stampfer MJ et al. Adherence to the Dietary Guidelines for Americans
and risk of major chronic disease in women. Am J Clin Nutr 2000; 72(5):1214–1222.
37. McCullough ML, Feskanich D, Rimm EB et al. Adherence to the Dietary Guidelines for Americans
and risk of major chronic disease in men. Am J Clin Nutr 2000; 72(5):1223–1231.
38. McCullough ML, Feskanich D, Stampfer MJ et al. Diet quality and major chronic disease risk in men
and women: moving toward improved dietary guidance. Am J Clin Nutr 2002; 76(6):1261–1271.
39. Fogli-Cawley JJ, Dwyer JT, Saltzman E et al. The 2005 Dietary Guidelines for Americans and insulin
resistance in the Framingham Offspring Cohort. Diabetes Care 2007; 30(4):817–822.
40. Liu S, Willett WC, Stampfer MJ et al. A prospective study of dietary glycemic load, carbohydrate
intake, and risk of coronary heart disease in US women. Am J Clin Nutr 2000; 71(6):1455–1461.
41. Meyer KA, Kushi LH, Jacobs DR, Jr., Slavin J, Sellers TA, Folsom AR. Carbohydrates, dietary fiber,
and incident type 2 diabetes in older women. Am J Clin Nutr 2000; 71(4):921–930.
42. Jenkins DJ, Kendall CW, Augustin LS et al. Glycemic index: overview of implications in health and
disease. Am J Clin Nutr 2002; 76(1):266S–273S.
43. Cho E, Smith-Warner SA, Spiegelman D et al. Dairy foods, calcium, and colorectal cancer: a pooled
analysis of 10 cohort studies. J Natl Cancer Inst 2004; 96(13):1015–1022.
44. Giovannucci E, Liu Y, Stampfer MJ, Willett WC. A prospective study of calcium intake and incident
and fatal prostate cancer. Cancer Epidemiol Biomarkers Prev 2006; 15(2):203–210.
45. Genkinger JM, Hunter DJ, Spiegelman D et al. Dairy products and ovarian cancer: a pooled analysis of
12 cohort studies. Cancer Epidemiol Biomarkers Prev 2006; 15(2):364–372.
46. Moorman PG, Terry PD. Consumption of dairy products and the risk of breast cancer: a review of the
literature. Am J Clin Nutr 2004; 80(1):5–14.
47. Feskanich D, Ziegler RG, Michaud DS et al. Prospective study of fruit and vegetable consumption and
risk of lung cancer among men and women. J Natl Cancer Inst 2000; 92(22):1812–1823.
48. Hung HC, Joshipura KJ, Jiang R et al. Fruit and vegetable intake and risk of major chronic disease.
J Natl Cancer Inst 2004; 96(21):1577–1584.
49. Smith-Warner SA, Spiegelman D, Yaun SS et al. Intake of fruits and vegetables and risk of breast cancer:
a pooled analysis of cohort studies. JAMA 2001; 285(6):769–776.
50. Terry P, Giovannucci E, Michels KB et al. Fruit, vegetables, dietary fiber, and risk of colorectal cancer.
J Natl Cancer Inst 2001; 93(7):525–533.
51. Voorrips LE, Goldbohm RA, van PG, Sturmans F, Hermus RJ, van den Brandt PA. Vegetable and fruit
consumption and risks of colon and rectal cancer in a prospective cohort study: The Netherlands Cohort
Study on Diet and Cancer. Am J Epidemiol 2000; 152(11):1081–1092.
52. Gambera PJ, Schneeman BO, Davis PA. Use of the Food Guide Pyramid and US Dietary Guidelines
to improve dietary intake and reduce cardiovascular risk in active-duty Air Force members. J Am Diet
Assoc 1995; 95(11):1268–1273.
53. Mensink RP, Katan MB. Effect of dietary fatty acids on serum lipids and lipoproteins. A meta-analysis
of 27 trials. Arterioscler Thromb 1992; 12(8):911–919.
54. Singh RB, Rastogi SS, Verma R et al. Randomised controlled trial of cardioprotective diet in patients
with recent acute myocardial infarction: results of one year follow up. BMJ 1992; 304(6833):1015–1019.
55. Burr ML, Fehily AM, Gilbert JF et al. Effects of changes in fat, fish, and fibre intakes on death and
myocardial reinfarction: diet and reinfarction trial (DART). Lancet 1989; 2(8666):757–761.
56. Kris-Etherton PM, Pearson TA, Wan Y et al. High-monounsaturated fatty acid diets lower both plasma
cholesterol and triacylglycerol concentrations. Am J Clin Nutr 1999; 70(6):1009–1015.
57. Rajaram S, Burke K, Connell B, Myint T, Sabate J. A monounsaturated fatty acid-rich pecan-enriched
diet favorably alters the serum lipid profile of healthy men and women. J Nutr 2001; 131(9):2275–2279.
58. Heine RJ, Mulder C, Popp-Snijders C, van der Meer J, van der Veen EA. Linoleic-acid-enriched diet:
long-term effects on serum lipoprotein and apolipoprotein concentrations and insulin sensitivity in
noninsulin-dependent diabetic patients. Am J Clin Nutr 1989; 49(3):448–456.
Chapter 10 / Food Guide Pyramids and the 2005 MyPyramid 207
59. Willett WC, Sacks F, Trichopoulou A et al. Mediterranean diet pyramid: a cultural model for healthy
eating. Am J Clin Nutr 1995; 61(6):1402S–1406.
60. de LM, Salen P, Martin JL, Monjaud I, Delaye J, Mamelle N. Mediterranean diet, traditional risk factors,
and the rate of cardiovascular complications after myocardial infarction: final report of the Lyon Diet
Heart Study. Circulation 1999; 99(6):779–785.
61. Esposito K, Marfella R, Ciotola M et al. Effect of a Mediterranean-style diet on endothelial dysfunction
and markers of vascular inflammation in the metabolic syndrome: a randomized trial. JAMA 2004;
292(12):1440–1446.
62. McManus K, Antinoro L, Sacks F. A randomized controlled trial of a moderate-fat, low-energy diet
compared with a low fat, low-energy diet for weight loss in overweight adults. Int J Obes Relat Metab
Disord 2001; 25(10):1503–1511.
63. Sierksma A, Patel H, Ouchi N et al. Effect of moderate alcohol consumption on adiponectin, tumor
necrosis factor-alpha, and insulin sensitivity. Diabetes Care 2004; 27(1):184–189.
64. Thadhani R, Camargo CA, Jr., Stampfer MJ, Curhan GC, Willett WC, Rimm EB. Prospective study
of moderate alcohol consumption and risk of hypertension in young women. Arch Intern Med 2002;
162(5):569–574.
65. Mezzano D, Leighton F, Martinez C et al. Complementary effects of Mediterranean diet and moderate
red wine intake on haemostatic cardiovascular risk factors. Eur J Clin Nutr 2001; 55(6):444–451.
66. Elkind MS, Sciacca R, Boden-Albala B, Rundek T, Paik MC, Sacco RL. Moderate alcohol consumption
reduces risk of ischemic stroke: the Northern Manhattan Study. Stroke 2006; 37(1):13–19.
67. Tapsell LC, Gillen LJ, Patch CS et al. Including walnuts in a low-fat/modified-fat diet improves HDL
cholesterol-to-total cholesterol ratios in patients with type 2 diabetes. Diabetes Care 2004; 27(12):2777–2783.
68. Cortes B, Nunez I, Cofan M et al. Acute effects of high-fat meals enriched with walnuts or olive oil on
postprandial endothelial function. J Am Coll Cardiol 2006; 48(8):1666–1671.
69. Pierce JP, Natarajan L, Caan BJ et al. Influence of a diet very high in vegetables, fruit, and fiber and
low in fat on prognosis following treatment for breast cancer: the Women’s Healthy Eating and Living
(WHEL) randomized trial. JAMA 2007; 298(3):289–298.
11 Nutrition Recommendations
for the General Population:
Where Is the Science?
Walter C.Willett and Meir J. Stampfer
KEY POINTS
• During the 1990s dietary guidelines for the US and many other countries promoted a diet low
in fat and high in “complex” carbohydrates.
• However, there was little evidence then that such a diet would promote health and reduce risk
of chronic disease, and subsequent data have not supported benefits for cardiovascular disease,
cancer, or weight control.
• Instead, the combination of controlled feeding studies of intermediate risk factors and prospective
epidemiologic studies has indicated that the type of dietary fat and dietary carbohydrate have
major impacts on risks of these diseases.
• Specifically, higher intake of trans fatty acids has adverse effects on blood lipids and inflammatory
factors, and has also been associated with greater risks of coronary heart disease and type 2
diabetes.
• In contrast, both types of studies have indicated beneficial effects of unsaturated fats, especially
polyunsaturated fats. The replacement of saturated fat with carbohydrates has little effect on the
ratio of serum total to HDL cholesterol, and is minimally associated with risk of heart disease.
• Similarly, higher intake of refined starches and sugar, represented by dietary glycemic load,
has adverse effects on blood lipids and inflammatory factors and is related to higher risks of
coronary heart disease and type 2 diabetes.
• Conversely, higher consumption of whole grains is related to lower risks of these diseases.
• Regrettably, this evidence has yet to be translated clearly into dietary guidance for many
populations.
Key Words: Diet, Dietary, Nutrition, Guidelines, Heart disease, Chronic disease
1. DIETARY GUIDANCE: WHERE IS THE SCIENCE?
In 1992, the United States Department of Agriculture (USDA) officially released its
first Food Guide Pyramid, which was intended to help the American public make food
choices that would maintain general good health and reduce risk of chronic disease (Fig. 1).
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_11,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
209
210 Willett and Stampfer
Fig. 1. USDA food pyramid.
Many other countries followed this lead; for example, the Iranian food guide pyramid
was a direct translation. The core message of the USDA pyramid was resoundingly
low fat: all fats and oils were to be consumed sparingly and, as replacement, “complex
carbohydrates” were to be consumed in abundance, 6–11 servings a day. Generous
amounts of vegetables (including more complex carbohydrates as potatoes), fruit, and
dairy products were encouraged, and at least three servings per day from the “meat”
group were advised, consisting of red meat, poultry, nuts, legumes, and eggs. Even at
the time when the pyramid was first released, we had long known that some types of
fat are essential, and that polyunsaturated fat could reduce plasma total cholesterol and
incidence of coronary heart disease. In contrast, there was little evidence that high intake
of starch is beneficial. Since 1992, evidence has continued to mount that the USDA
pyramid provided misleading guidance to those seeking healthy food choices.
How did the pyramid go so wrong? Facing an epidemic of high cholesterol and coronary
heart disease, and knowing that dietary saturated fats raise blood levels of cholesterol,
Chapter 11 / Nutrition Recommendations for the General Population: Where Is the Science? 211
policy makers sought to reduce dietary saturated fat. Apparently, however, it was
considered too difficult to educate the public about the subtleties of types of fat. Instead,
the thinking went, since saturated fat represented such a large fraction of dietary fat, if
we advocate low fat, saturated fat intake would drop. Also, in the early 1980s, based
largely on comparisons between countries, the belief developed that total fat in the diet
was the primary factor underlying the high rates of breast, colon, and prostate cancer in
Western counties. This led to a clear, simple message that fat is bad. Because protein in
the diet is relatively constant (and often associated with saturated fat), the notion that
fat is bad led to the corollary that carbohydrates are good, even without direct evidence.
At the time the pyramid was developed, the typical US diet contained about 40% of
calories from fat. It was thought that with a concerted campaign, we might have 30%
as a reasonable goal. This led to the widespread adoption of 30% of calories from fat as
a limit. The 30% limit became so entrenched in dietary guidelines in the US, and many
other countries that even the sophisticated observer could be forgiven for thinking that
there must be many studies showing that individuals with that level of fat intake enjoyed
better health than those with higher levels. In fact, there were no such studies at all.
2. DIETARY FAT AND CORONARY HEART DISEASE
The concept that fat in general is to be avoided derives largely from observations
that affluent Western countries have both high intakes of fat and high rates of coronary
heart disease. However, this correlation was limited to saturated fat, and countries with
high intake of monounsaturated fat tended to have lower rates. In the seminal study
conducted by Keys and colleagues, the two regions with the lowest rates of heart disease
were those following the traditional diets of Japan, with about 8–10% of calories from
fat, and the traditional diet of Crete, with approximately 40% calories from fat (Fig. 2).
International comparisons need to be interpreted cautiously, nevertheless, because many
factors, such as smoking rates, physical inactivity, and adiposity, are also correlated with
western affluence.
Evidence from early controlled feeding studies in the 1960s documented the adverse
effects of saturated fat on total serum cholesterol levels, which are associated with higher
risk of coronary heart disease, but also showed that polyunsaturated fat reduces serum
cholesterol. Thus, dietary advice during the 1960s and 1970s emphasized replacement of
saturated fat with polyunsaturated fat, not total fat reduction. The subsequent doubling
of polyunsaturated fat consumption in the US probably contributed greatly to the halving
of coronary heart disease rates in the US (1). For reasons described earlier, in the 1980s
dietary advice subtly shifted to replacing fat in general with carbohydrate, which is the
foundation of the USDA pyramid. The wisdom of this direction became questionable
with the appreciation that total serum cholesterol can be subdivided: the LDL fraction
increases but the HDL fraction reduces risk of coronary disease. More recently, serum
triglyceride levels have also been associated with higher risk. Controlled feeding studies
have shown that when saturated fat is replaced by carbohydrate, total and LDL cholesterol
levels do fall, but HDL also falls proportionally, and triglyceride levels rise (2). Thus,
the ratio of LDL or total cholesterol to HDL does not change, which would predict little
reduction in heart disease risk. Replacing either poly or monounsaturated fat with carbo-
hydrate would actually make the serum cholesterol ratio worse, but replacing saturated
212 Willett and Stampfer
Y = 10-YEAR CORONARY INCIDENCE PER 10,000 MEN
3000
east E
Finland
Y= 64+27X
r = 0.39
2000
West W
Finland
Italy 1 C Holland N
1000 Italy 2 M Corfu
Belgrade, Yugoslavia 3
Italy 3 R B
G Z Yugoslavia 4
D
Japan 1 J Yugoslavia 2 S
Yugoslavia 1 V Slavonia
T
Japan 2 Crete K
0
0 10 20 30 40
X = % DIET CALORIES FROM TOTAL FATS
Ten-year incidence rate of coronary heart disease, by any diagnostic criterion,
plotted against the percentage of dietary calories supplied by total fats.
(Keys, 1980)
Fig. 2. Ten-year incidence of coronary heart disease, by any diagnostic criterion, plotted against
the percentage of dietary calories supplied by total fats (Keys, 1980).
fat with either polyunsaturated or monounsaturated fat improves this ratio and would
be expected to reduce heart disease. The relation of dietary fat to heart disease became
more complicated with the appreciation that trans-unsaturated fatty acids (produced
by the partial hydrogenation of liquid vegetable oils) have important biological effects.
Trans fats have uniquely adverse characteristics because they raise serum LDL and
triglycerides and reduce HDL (3).
Although the effects of diet on blood cholesterol fractions and triglycerides are
important, we now know that dietary factors can influence many other pathways that
are important in the cause and prevention of coronary heart disease (Fig. 3, multiple
pathways) (4). For example, omega-3 fatty acids (from fish and some plant oils) can
reduce the likelihood of ventricular fibrillation (and therefore sudden cardiac death),
and there is now solid evidence that trans fats also increase inflammatory factors (5,6),
which appear to increase risks of cardiovascular disease and type 2 diabetes. Thus, it is
also important to assess directly the relation of diet to heart disease incidence because
this will integrate all the adverse and beneficial effects of a dietary factor. Ideally, studies
of diet and heart disease would be conducted as trials in which individuals are randomly
assigned to one diet or another and followed for many years. Because of practical
constraints and cost, few such studies have been conducted, and most of these have been
in patients with existing heart disease. Although limited, these studies have supported
benefits of replacing saturated fat with polyunsaturated fat, but not with carbohydrate
(7). The best alternative is usually to conduct large prospective observational studies in
which the diets of many persons are assessed periodically over time and participants are
Chapter 11 / Nutrition Recommendations for the General Population: Where Is the Science? 213
Blood lipids
Blood pressure
Thrombotic tendency
Insulin resistance
Diet CHD
Oxidation
Homocysteine
Inflammation / endothelial dysfunction
Ventricular irritability & arrhythmia
Fig. 3. Pathways leading from diet to incidence of coronary heart disease (CHD).
monitored for the development of heart disease and other conditions. In these studies,
smoking, physical activity, and other potential risk factors can be measured and accounted
for in the analysis. Thus, we have followed nearly 90,000 women who first completed
detailed questionnaires on diet in 1980 and over 50,000 men who were enrolled in 1989.
After adjusting for smoking, physical activity, and other recognized risk factors, we
found strong relationships between type of dietary fat and risk of heart disease in the
direction predicted by the controlled feeding studies. Specifically, compared with the
same percentage of energy from carbohydrate, intake of trans fats was strongly associated
with greater risk of coronary heart disease, saturated fat was only weakly related to risk,
and both monounsaturated and polyunsaturated fats were associated with lower risk (8).
Because of the opposing relationships for specific types of fat, the percentage of calories
from total fat was not associated with risk of heart disease. This adds further support to
the conclusion of a report by the National Academy of Sciences in 1989 that total fat
intake per se is not a determinant of coronary heart disease (9). Although the relation of
intake of trans fat to risk of coronary heart disease was initially controversial, this has
been reproduced multiple times (5).
3. DIETARY FAT AND CANCER
As for coronary heart disease, the belief that dietary fat is a major cause of cancer was
derived largely from correlations among countries between per capita intake of total and
animal fat and rates of cancers common in affluent countries, including cancers of the
breast, colon, and prostate. However, in large prospective studies in which confounding
variables could be better controlled, there has consistently been little relation between
214 Willett and Stampfer
intakes of total and specific types of fat during mid life and risks of cancers of the breast
and colon (10). Data on diet and prostate cancer remain limited, but some studies
have suggested positive associations with animal fat. Thus, it is reasonable to make
decisions about dietary fat primarily on the basis of its effects on cardiovascular disease,
not cancer.
4. DIETARY FAT AND BODY FAT
Excess body fat, including both mild overweight and obesity, is the most important
nutritional problem in the US and an increasing number of countries, because it is a major
risk factor for many diseases including type 2 diabetes, coronary heart disease, cancers
of the breast, colon, kidney, esophagus, and endometrium, osteoarthritis, cataracts, and
many other conditions. Dietary fat has been believed to be an important contributor to
overweight because it contains more calories per gram and also it may be more
efficiently stored as fat than carbohydrate. However, it is now clear that any differences
in metabolic efficiency are not practically important and that the balance of total calories
rather than just fat calories are important in weight control (11). Thus, the critical issue
is whether the fat composition of the diet influences our ability to control caloric intake,
and theories abound why one diet should be better than another. Long-term empirical
data are essential, but remarkably sparse. In randomized trials, individuals assigned to
low fat diets often tend to loose a few pounds during the first months, but then regain
their weight. In randomized trials lasting a year or longer, there has consistently been no
greater weight loss with low fat diets (11,12).
5. CARBOHYDRATES
Because adequate caloric intake is essential, a substantial reduction in dietary fat
practically implies an increase in carbohydrate. Because of concerns about consumption
of “empty calories” from sugar, high intake of “complex carbohydrates,” mainly starch
in the form of bread, rice, pasta and crackers, formed the base of the 1992 USDA
pyramid. However, refined carbohydrates, such as white bread and white rice, are rapidly
metabolized to simple sugars and cause a greater rise in blood glucose and insulin levels
than grains that have not been milled into fine flour. In addition to producing a rapidly
absorbed form of starch, the refining process also removes many vitamins and minerals
and fiber. Indeed, potatoes raise blood sugar levels more rapidly than the same amount
of calories from table sugar. The rapid rise in blood sugar stimulates insulin release, and
a consequent sharp decline in blood sugar, sometimes even going below baseline. These
sharp swings in glucose and insulin have deleterious metabolic consequences, raising
triglycerides, and lowering HDL. The precipitous decline in glucose can also lead to more
hunger after a carbohydrate rich meal, and may contribute to overeating and obesity.
Thus, the concept of “complex carbohydrates” is not based on sound physiological
principles. A different way to classify carbohydrates is by their propensity to raise blood
sugar levels. Foods have a specific glycemic index, reflecting this propensity compared
with a standard. The glycemic index depends not only on the chemical composition, but
also on the physical form of the food (13). The glycemic load takes into account both the
glycemic index of the food, and the amount of carbohydrate. In our large prospective studies,
we have found that high intake of starches from refined grains and potatoes (i.e., a high
Chapter 11 / Nutrition Recommendations for the General Population: Where Is the Science? 215
glycemic load) is associated with higher risk of type 2 diabetes and coronary heart disease,
and that greater intake of cereal fiber is related to lower risk of these conditions (14,15).
As noted earlier, replacement of dietary fat with carbohydrate creates the adverse
metabolic picture of low serum HDL and high triglycerides. Recent evidence also indicates
that this adverse metabolic response to carbohydrate is substantially worse among
persons who already have a greater degree of insulin resistance, mainly as the result of
overweight and inactivity (16–19). This can account for the ability of traditional farmers in
Asia and elsewhere, who have been extremely lean and active, to consume large amounts
of carbohydrate without experiencing diabetes or heart disease, whereas the same diet
in a more sedentary population can have deleterious effects.
6. FRUITS AND VEGETABLES
High intake of fruits and vegetables is perhaps the least controversial aspect of the
dietary pyramid, and reduction in cancer risk has been a widely promoted benefit. However,
most of the evidence for a cancer benefit has come from case–control studies, in which
patients with cancer and selected control subjects are asked about their earlier diets.
These retrospective studies are susceptible to numerous biases, and recent findings from
large prospective studies have tended to show little relation between overall fruit and
vegetable consumption and cancer incidence (20). Although some benefits probably
exist for specific components of some fruits and vegetables and risks, the benefit of a
general increase in fruit and vegetable consumption has probably been overstated. One
component that does seem to be beneficial for reducing risk of colon and possibly other
cancers is folic acid, but vitamin supplements and fortified foods are the major source
of this vitamin in the US.
Although the benefits of fruits and vegetables for cancer prevention are probably
small, substantial evidence from cohort studies indicates that higher intake will reduce
risks of cardiovascular disease (20). This benefit is probably due to many constituents,
but folic acid and potassium appear to be contributing factors. Inadequate folic acid is
also responsible for higher risks of serious birth defects, and low intake of lutein, a pig-
ment in green leafy vegetables, has been associated with greater risks of cataracts and
degeneration of the retina. Thus, there are many reasons, besides being a primary source
of many vitamins needed for good health, to consume the recommended five servings
per day of fruits and vegetables, even if this has little impact on cancer risk. However,
the inclusion of potatoes as a vegetable in the USDA pyramid had little justification as
they are mainly consumed as a source of starch and do not contribute to the benefits seen
for other vegetables. Not surprisingly, we have found that greater intake of potatoes was
associated with higher risk of type 2 diabetes (21).
Low carbohydrate diets have been popular for weight control, although the long-term
effects on weight are not clear, and concerns have been raised that these diets might
increase risks of heart disease because they are often high in saturated fat and cholesterol.
However, within the Nurses’ Health Study (22) we found that low carbohydrate diets
were not associated with risk of coronary heart disease, probably because the reduction
in glycemic load balanced the higher intakes of saturated fat and cholesterol. When the
sources of fat and protein were mainly from vegetable sources, we found that a reduced
carbohydrate intake was associated with a lower risk of heart disease.
216 Willett and Stampfer
7. PROTEIN SOURCES
Although treated equally by the USDA pyramid, the health consequences of consuming
red meat, poultry, fish, legumes, nuts, and eggs are quite different. High consumption
of red meat has been associated with increased risk of coronary heart disease, probably
because of its content of saturated fat and cholesterol, and higher risk of type 2 diabetes
and cancers of the colon and possible prostate. The elevated risk of colon cancer does
not seem to be due to the fat content of red meat; processed meats may be particularly
related to this cancer. In contrast, the fat in poultry and fish is more unsaturated than that
in red meat, and fish is an important source of the essential omega-3 fatty acids. Not
surprisingly, we have seen that those who replace red meat with chicken and fish have a
lower risk of coronary heart disease and colon cancer. Eggs are high in cholesterol, but
consumption up to one per day does not appear to have adverse effects on heart disease
risk (except among diabetics), probably because the effects of a slightly higher cholesterol
level are counter balanced by other nutritional benefits. Many people have avoided nuts
because of their high fat content, but the fat in nuts, including peanuts, is mainly unsaturated,
and walnuts in particular are a good source of omega-3 fatty acids. In controlled feeding
studies, nuts improve blood cholesterol fractions, and in multiple cohort studies those
who consume more nuts have lower risks of heart disease. Thus, treating these various
sources of proteins as equals fails to provide the public with information needed for
healthy choices.
8. DAIRY FOODS
The USDA pyramid promoted high consumption of dairy products, which has usually
been justified by their high content of calcium and the prevention of osteoporosis and
fractures. Although the highest rates of fractures are found in countries with high dairy
food consumption, large prospective studies have consistently not shown a lower risk
of fractures among those with high intake of dairy products and thus more studies are
needed (23). Calcium is an essential nutrient, but the US adequate intake of calcium
for bone health (1,200 mg/day for persons over 50 years of age) has probably been
overstated by reliance on short-term studies, whereas British and other EU countries’
adequate intakes range between 700 and 800 mg/day. If a person needs more calcium,
this can also be obtained at lower cost and without saturated fat or calories by taking a
supplement. Several lines of evidence now suggest that low calcium intake can modestly
increase risk of colon cancer (24), but most of the benefit of higher intake appears to be
achieved by a good overall diet plus the equivalent of about one or two glasses of milk,
or one or two portions of dairy products per day, which would correspond approximately
to the UK definition of adequate intake of about 700 mg/day.
Higher than the recommended (see below) consumption of dairy products cannot a
priori be assumed to be safe and effective because we are only now beginning to have
the data to evaluate the consequences of high intake throughout life. In several studies,
despite lower risk for colon cancer, men who consume high amounts of calcium or dairy
products have experienced increased risk of prostate cancer (25) and in some cohort
studies women with high intakes have had higher rates of ovarian cancer. Although fat
was initially assumed to be the responsible factor, this has not been supported in more
detailed analyses; high calcium intake itself seemed most clearly related to risk of prostate
Chapter 11 / Nutrition Recommendations for the General Population: Where Is the Science? 217
cancer. In contrast, low calcium intake is related to risk for colon cancer. The role of
calcium, vitamin D, and dairy products in health and disease is thus an area in need of
more research. At the moment, the authors consider it imprudent to recommend more
than two servings per day.
9. THE OVERALL IMPACT OF FOLLOWING THE USDA FOOD
PYRAMID
With strong support from many elements of the food industry, the USDA food guide
pyramid became a highly recognized icon. Many studies have assessed how well its
message was adopted by the American public, but few studies have evaluated the health
of individuals who followed those guidelines, compared with others. Some benefits
seem likely: by decreasing total fat intake consumption of saturated and trans fat will
be reduced, and fruits and vegetables will be increased. However, the pyramid could
also have led people to reduce desirable unsaturated fats and to increase consumption of
refined starches, so that the benefits might be counterbalanced by harm.
To evaluate the overall impact of following the Pyramid message, we used the Healthy
Eating Index (HEI), a score developed by the USDA, to measure adherence to the
Pyramid and its accompanying dietary guidelines in federal nutrition programs. From
the data collected in our large cohort studies, we calculated each participant’s Healthy
Eating Index score and then examined the relation of these scores to subsequent risk of
major chronic disease, defined as any heart attack, stroke, cancer, or nontraumatic death
from any cause (25–27). In analyses adjusted only for age, women and men with the
highest healthy eating index score did experience lower risks of major chronic disease.
However, these individuals also smoked less, exercised more, and had generally healthier
lifestyles; after adjusting for these variables, participants with the highest HEI scores
did not experience significantly better overall health outcomes. This is consistent with
a counterbalancing of benefits and harm from following the USDA pyramid, and a lost
opportunity to improve health.
10. THE 2005 USDA MYPYRAMID AND AN ALTERNATIVE
Because the scientific evidence had become so discordant with the 1992 Food Guide
Pyramid, in 2005 the USDA released a new graphic and corresponding Website called
MyPyramid (http://www.mypyramid.gov/). An advantage of this new graphic is that
the admonition to avoid dietary fat and eat large amounts of starch is no longer present.
However, this new graphic consists of nothing more than colorful bands on a pyramid,
and thus provides no dietary guidance at all. This represents a lost educational opportunity,
but is consistent with the stated policy perspective of the USDA, which is that there is no
such thing as a good for or a bad food, and that all foods can be part of a healthy diet.
Because of the serious deficiencies of the USDA pyramids, we have attempted to de-
velop alternatives derived from the best available evidence. Thus our alternative Healthy
Eating Pyramid (Fig. 4) emphasizes weight control, giving attention to calories from all
sources, and regular physical activity; healthy fats and healthy forms of carbohydrate; an
abundance of fruits and vegetables; healthy sources of protein, which can be consistent
with either a vegetarian or omnivore diet; and suggests sparing use of red meat, butter,
refined grain products, potatoes, and sugar. Trans fat does not appear because it has no
218 Willett and Stampfer
Fig. 4. Healthy eating pyramid.
place in an optimally healthy diet. A multiple vitamin is suggested for most people and
moderate alcohol consumption is an option if not contraindicated. Data supporting the
cardioprotective effects of moderate alcohol (in any form, wine, beer, or spirits) continues to
accumulate. Policy makers are acutely aware of the risks entailed in promoting moderate
alcohol consumption, so the pyramid is silent on this issue. Although clearly no alcohol
is better than too much, a strong case can be made for including moderate consumption
as part of a healthy diet for those without contraindications. One health risk associated
with moderate consumption is an increase in breast cancer, but it appears this may be
conteracted with adequate folate intake.
To evaluate the overall impact of this alternative approach to food choices on risk of
chronic disease, we have created a revised dietary score based on our Healthy Eating
pyramid (28). Better adherence to this alternative index of healthy food choice was
associated with lower risk of risk of major chronic disease in both men and women, but
the benefits were due to reduced risk of cardiovascular disease, not cancer. Avoidance
Chapter 11 / Nutrition Recommendations for the General Population: Where Is the Science? 219
of overweight and regular physical activity, rather than specific food choices, is related
to lower risk of many important cancers.
11. FUTURE NEEDS
Much research on the relation of diet to health remains; almost all aspects are in need
of additional refinement and many uncertainties exist. Important topics include the role
of dairy products, the effects on health of specific fruits and vegetables, the risks and
benefits of vitamin supplements, and the effects of all aspects of diet during childhood
and early adult life. The interaction of dietary factors with genetic predisposition is a
topic of great interest, although its importance remains to be determined.
The amount of ongoing research on diet and health is massive, and this should provide
improved and more specific dietary guidance in the future. It will be important to evaluate
the validity of this information in relation to long-term health outcomes empirically.
An additional challenge will be to convey this information to the public in a way that
is strictly based on the best available scientific evidence. Agriculture is by far the largest
and most powerful industry in the country, making it difficult for the Department of
Agriculture to develop objective nutritional guidelines because of its dual role as an
industry advocate and provider of guidance to consumers. Dietary guidance should be
developed in a setting that is insulated from political and economic interests.
12. CONCLUSION
A wealth of research from many lines of investigation indicates that dietary choices
have an important impact on our long-term health. However, the Department of
Agriculture has provided poor guidance to persons seeking to maintain or improve their
long-term health. Alternative national guidelines that emphasize healthy forms of
carbohydrate, fats, and protein are needed.
REFERENCES
1. Hetzel BS, Charnock JS, Dwyer T, et al. Fall in coronary heart disease mortality in U.S.A. and Australia
due to sudden death: evidence for the role of polyunsaturated fat. J Clin Epidemiol 1989;42:885–93.
2. Mensink RP, Katan MB. Effect of dietary fatty acids on serum lipids and lipoproteins: a meta-analysis
of 27 trials. Arterioscler Thromb 1992;12:911–9.
3. Mensink RP, Zock PL, Kester AD, et al. Effects of dietary fatty acids and carbohydrates on the ratio of
serum total to HDL cholesterol and on serum lipids and apolipoproteins: a meta-analysis of 60 controlled
trials. Am J Clin Nutr 2003;77:1146–55.
4. Hu FB, Willett WC. Optimal diets for prevention of coronary heart disease. JAMA 2002;288:2569–78.
5. Mozaffarian D, Katan MB, Ascherio A, Stampfer MJ, et al. Trans fatty acids and cardiovascular disease.
N Engl J Med 2006;354:1601–13.
6. Baer DJ, Judd JT, Clevidence BA, et al. Dietary fatty acids affect plasma markers of inflammation in
healthy men fed controlled diets: a randomized crossover study. Am J Clin Nutr 2004;79:969–73.
7. Sacks FM, Katan MB. Randomized clinical trials on the effects of dietary fat and carbohydrate on plasma
lipoproteins and cardiovascular disease. Am J Med 2002;113 Suppl 9B:13S–24.
8. Hu FB, Stampfer MJ, Manson JE, et al. Dietary fat intake and the risk of coronary heart disease in
women. N Eng J Med 1997;337:1491–9.
9. National Research Council (U.S.), Committee on Diet and Health. Diet and health: implications for
reducing chronic disease risk. Washington, DC: National Academy Press, 1989.
220 Willett and Stampfer
10. Kim EH, Willett WC, Colditz GA, et al. Dietary fat and risk of postmenopausal breast cancer in a
20-year follow-up. Am J Epidemiol 2006;164:990–7.
11. Willett WC, Leibel RL. Dietary fat is not a major determinant of body fat. Am J Med 2002;113 Suppl
9B:47S–59.
12. Dansinger ML, Gleason JA, Griffith JL, et al. Comparison of the Atkins, Ornish, Weight Watchers, and
Zone diets for weight loss and heart disease risk reduction: a randomized trial. JAMA 2005;293:43–53.
13. Ludwig DS. The glycemic index – Physiological mechanisms relating to obesity, diabetes, and cardio-
vascular disease [Review]. JAMA 2002;287:2414–23.
14. Schulze MB, Liu S, Rimm EB, et al. Glycemic index, glycemic load, and dietary fiber intake and
incidence of type 2 diabetes in younger and middle-aged women. Am J Clin Nutr 2004;80:348–56.
15. Liu S, Willett WC, Stampfer MJ, et al. A prospective study of dietary glycemic load, carbohydrate
intake, and risk of coronary heart disease in US women. Am J Clin Nutr 2000;71:1455–61.
16. Jeppesen J, Schaaf P, Jones G, et al. Effects of low-fat, high-carbohydrate diets on risk factors for
ischemic heart disease in postmenopausal women. Am J Clin Nutr 1997;65:1027–33.
17. Willett WC, Stampfer M, Chu N, et al. Assessment of questionnaire validity for measuring total fat
intake using plasma lipid levels as criteria. Am J Epidemiol 2001;154:1107–12.
18. Liu S, Manson JE, Stampfer MJ, et al. Dietary glycemic load assessed by food frequency questionnaire
in relation to plasma high-density lipoprotein cholesterol and fasting triglycerides among postmeno-
pausal women. Am J Clin Nutr 2001;73:560–6.
19. Oh K, Hu FB, Cho E, et al. Carbohydrate intake, glycemic index, glycemic load, and dietary fiber in
relation to risk of stroke in women. Am J Epidemiol 2005;161:161–9.
20. Hung HC, Joshipura KJ, Jiang R, et al. Fruit and vegetable intake and risk of major chronic disease.
J Natl Cancer Inst 2004;96:1577–84.
21. Halton TL, Willett WC, Liu S, et al. Potato and french fry consumption and risk of type 2 diabetes in
women. Am J Clin Nutr 2006;83:284–90.
22. Halton TL, Willett WC, Liu S, et al. Low-carbohydrate-diet score and the risk of coronary heart disease
in women. N Engl J Med 2006;355:1991–2002.
23. Hegsted DM. Calcium and osteoporosis. J Nutr 1986;116:2316–19.
24. Cho E, Smith-Warner S, Spiegelman D, et al. Dairy foods and calcium and colorectal cancer: a pooled
analysis of 10 cohort studies. J Natl Cancer Inst 2004; 96:1015–22
25. Giovannucci E, Liu Y, Stampfer MJ, et al. A prospective study of calcium intake and incident and fatal
prostate cancer. Cancer Epidemiol Biomarkers Prev 2006;15:203–10.
26. McCullough ML, Feskanich D, Rimm EB, et al. Adherence to the Dietary Guidelines for Americans
and risk of major chronic disease in men. Am J Clin Nutr 2000;72:1223–31.
27. McCullough ML, Feskanich D, Stampfer MJ, et al. Adherence to the Dietary Guidelines for Americans
and risk of major chronic disease in women. Am J Clin Nutr 2000;72:1214–22.
28. McCullough ML, Feskanich D, Stampfer MJ, et al. Diet quality and major chronic disease risk in men
and women: moving toward improved dietary guidance. Am J Clin Nutr 2002;76:1261–71.
12 Nutrition Recommendations and
Interventions for Subjects with
Cardiovascular Disease
Meropi Kontogianni, Mary Yannakoulia,
Lauren Kuhn, Sunali Shah, Kristina Day,
and Christos S. Mantzoros
KEY POINTS
• Diet influences cardiovascular health through a number of mechanisms.
• Nutrition recommendations are of major importance both in primary and secondary prevention
of cardiovascular disease (CVD).
• A great body of research has examined the role of specific nutrients, including fat, carbohydrates,
fiber, and alcohol, in reducing CVD risk.
• More recently the focus has shifted to the effect of food groups, such as fruits and vegetables,
whole grains, and nuts and dairy products, and favorable dietary patterns that combine a
variety of nutrients. In this perspective, a “prudent” dietary pattern, characterized by high
intakes of fruits, vegetables, legumes, fish, poultry and wholegrain cereals, has been associated
with significantly lower risks for CVD factors.
• Mediterranean dietary patterns, as well as the DASH (Dietary Approaches to Stop Hypertension)
pattern, have been proven to exert significant cardioprotective effects in secondary prevention
of CVD.
• Achieving and maintaining a healthy body weight change (as an initial goal to reduce body
weight by ~10% from baseline), an active lifestyle (a minimum of 30 min of physical activity
for most days of the week), and a balanced diet constitute the goals of the intensive counseling
recommended for individuals with CVD.
• Effective interventions should combine nutrition education with behavior-oriented counseling
to help patients acquire the skills, motivation, and support needed to alter their lifestyle patterns.
Key Words: Cardiovascular disease, Nutrition, Mediterranean diet, DASH diet
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_12,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
221
222 Kontogianni et al.
1. INTRODUCTION: PREVENTION
Industrial and technological revolutions have resulted in dramatic shifts in the prevalence
of several diseases over the last decades. Cardiovascular disease (CVD), in particular, has
emerged as the dominant chronic disease in many parts of the world. Diet, tobacco smoking,
physical inactivity, obesity, as well as hyperlipidemia, hypertension, and diabetes mellitus
have contributed to the increasing morbidity and mortality from CVD. Thus, appropriate
alterations of lifestyle and nutritional practices are of major importance in primary pre-
vention of CVD. What a person routinely eats appears to play a central role in his or her
long-term risk of CVD. Although much of the focus from the 1950s to the 1990s was on
the contribution the diet made to blood levels of total cholesterol or low-density lipoprotein
cholesterol (LDL-C), it has now been realized that this relationship is only one aspect of
the diet’s role in contributing to CVD risk. Diet is thought to influence coronary heart
disease through a number of mechanisms, including abnormal lipid levels, raised blood
pressure, thrombotic tendency, endothelial dysfunction, systemic inflammation, insulin
resistance, altered cardiac rhythm, and elevated oxidative stress (1).
Substantial research has examined the role of diet on CVD risk in terms of nutrients,
food groups, or dietary patterns. On the one hand, nutrients including saturated fatty
acids, trans fatty acids, and sodium have been proven to most significantly heighten CVD
risk, resulting in detrimental increases in blood cholesterol levels and blood pressure.
On the other hand, there are numerous beneficial nutrients including dietary fiber, vari-
ous antioxidants (e.g., vitamins A, C and E), B vitamins (B6, B12, and niacin), folic acid,
omega-3 fatty acids, monounsaturated fatty acids, calcium, and potassium. Food groups
such as fruits, vegetables, low fat dairy products, nuts, whole-grain cereals, fatty fish,
and olive oil have been linked to reduced CVD risk in many epidemiological studies
(2). Finally, studies examining the effect of the overall diet on CVD risk have revealed
that adherence to a “prudent” dietary pattern (characterized by higher intake of fruits,
vegetables, legumes, whole grains, poultry, and fish), to a DASH-style diet, or to the
Table 1
Major Dietary Recommendations for CVD Risk Prevention
Aim for balance between calorie intake and physical activity to achieve or maintain a
healthy body weight. For overweight or obese subjects, a weight reduction program
should be initiated
A wide variety of food items should be eaten
Consumption of a diet rich in vegetables and fruits, wholegrain cereals, and bread is
recommended
Consumption of fish, especially oily fish, at least twice a week, lean meat and low fat dairy
products should be emphasized
Limit saturated (animal) fat and partially hydrogenated fat intake by preferring the above-
mentioned foods, as well as monounsaturated and polyunsaturated fats from vegetable
and marine sources. Saturated fat should not exceed 10% of daily caloric intake
Reduction in beverage intake and in foods with added sugars is desirable
Foods should be prepared with little or no salt. Emphasis needs to be placed on fresh or fro-
zen unsalted foods. Many processed and prepared foods, including bread are rich in salt
In case of habitual alcohol consumption, this should be done in moderation
Chapter 12 / Nutrition Recommendations and Interventions 223
traditional Mediterranean diet is associated with a lower risk of coronary heart disease
and stroke and with greater life expectancy, independent of other lifestyle factors (3–5).
It should be noted, however, that evidence deriving from observational epidemiology
studies has not always been confirmed by interventional trials.
According to the guidelines of the American Heart Association and the European
Society of Cardiology, dietary changes constitute an integral part of cardiovascular risk
management (2,6). All individuals at high risk for CVD should be given professional and
individualized advice on the food options that best reduce cardiovascular risk. A varied
and energy-balanced regimen, together with regular exercise, is of critical importance
for the preservation of cardiovascular health (Table 1). Moreover, intentional weight
loss in obese patients can improve or prevent many of the obesity-related risk factors
for CVD. It is now clear that body fat, and in particular intraabdominal visceral fat, is a
metabolically active endocrine organ that is capable of synthesizing and releasing into
the bloodstream an important array of peptide and non-peptide compounds that may
play a role in cardiovascular homeostasis.
2. ASSESSMENT
The assessment and subsequent treatment of CVD begins with the identification of risk
factors, particularly those that are nutrition-related. Careful and detailed assessment of
nutritional status should focus on potential risk factors including diabetes, overweight/obes-
ity, hypertension, and prothrombotic or proinflammatory states including elevated homo-
cysteine levels, and should consider food choices, physical activity levels, and patients’
readiness to change their habits toward a healthier pattern. Overweight is classified as a
body mass index (BMI) of 25.0–29.9 kg/m2. Class 1 obesity refers to a BMI of 30.0–34.9,
class 2 obesity to a BMI of 35.0–39.9, and class 3, or extreme obesity, to a BMI of >40 kg/
m2(7). A BMI of >30 kg/m2 or >27 kg/m2, along with comorbidities, calls for immediate
initiation of weight management including pharmacological therapy. Weight management
with life style modifications should also be considered for those subjects with BMI ³ 25
kg/m2. Moreover, the association between both increased waist circumference (WC) or
waist to hip ratio (WHR) and greater risk of CVD development has been demonstrated in
both cohort and case-control studies. Evidence from these sources shows WC to be a better
marker of intraabdominal fat content than WHR. In the context of cardiovascular health,
WC is shown to be an extremely useful marker of risk. Unlike BMI alone, WC is able to
reflect visceral fat accumulation, which is associated with increased CVD risk and related
metabolic risks to a greater extent than simply subcutaneous body fat alone. Larger WCs
(>40 in. for men and > 35 in. for women) are closely linked to insulin resistance, sleep
apnea, and inflammation, which are parti-cularly dangerous for the patient with coronary
heart disease (CHD) (7). Nutritional risk factors such as high intake of saturated fatty acids
(SFA), trans fatty acids (TFA), cholesterol, and sodium as well as low intake of protective
foods such as soluble fiber, fatty acids (including omega-3, or n-3) and a variety of fruits
and vegetables should be thoroughly assessed through detailed diet histories (1).
3. GOALS OF NUTRITION INTERVENTION
There is a wide variety of lifestyle and pharmacological treatments available for
the prevention and treatment of CHD. The combination of nutrition management and
behavioral modification with appropriate pharmacotherapy has been shown to be the
224 Kontogianni et al.
Table 2
Dietary Recommendations for Achieving Desirable Blood Lipid Profile and Especially
LDL-C Levels (8)
Limit food items high in saturated fats
Replace saturated fats with lower-fat foods
Increase consumption of food items with unsaturated fat
Carefully monitor intake of food items high in cholesterol
Severely limit food items containing trans fatty acids
Increase food items rich in viscous fiber
Increase food items containing stanol/sterol esters (special margarines, fortified orange
juice, special cocoa/chocolate bars)
In case of hypetriglyceridemia:
Limit dietary fat intake between 25 and 35% of total daily calories, as well as simple
sugars and rapidly hydrolyzed starches, which have a greater glycemic effect than
more complex carbohydrates
Limit excessive alcohol intake, which has a detrimental effect on triglycerides levels
There is accumulating evidence to support the beneficial influence of omega-3
fatty acids in the management of hypertriglyceridemia either through diet
or supplements, but very high doses may be needed (see relevant chapter
on pharmacotherapy)
Table 3
Therapeutic Lifestyle Changes for Patients with Already Established CVD (9)
Nutrient Recommended Intake as percent of total calories
Total fata 25–35%
Saturated fat Less than 7%
Polyunsaturated fat Up to 10%
Monounsaturated fat Up to 20%
Carbohydratesb 50–60% of total calories
Proteinc ~15%
Cholesterol Less than 200 mg/day
Plant stanols/sterols 2 g/day
Increased soluble fiber 10–25 g/day
Total calories Balance energy intake and expenditure to
maintain desirable body weight and to
prevent weight gain
Physical activity Include enough moderate exercise to expend
at least 200 kcal/day
a
The 25–35% fat recommendation allows for increased intake of unsaturated fat in place of
carbohydrates in people with the metabolic syndrome or diabetes.
b
Carbohydrates should come mainly from foods rich in complex carbohydrates. These include grains
(especially whole grains), fruits, and vegetables.
c
Soy protein may be used as a replacement for some animal products.
Chapter 12 / Nutrition Recommendations and Interventions 225
most effective method of treatment. For patients with already-established CHD or
dyslipidemia, it is recommended that dietary and lifestyle changes are made first, and
pharmacologic treatment is added as needed (8,9). Tables 2 and 3 summarize the dietary
recommendations for patients with hyperlipidemia and already-established CHD, respec-
tively. Pharmacotherapy is beyond the scope of this Chapter.
Dietary intervention by a registered dietitian, usually over the course of two to six ses-
sions, has been shown to be most effective at helping patients achieve these goals. Nutri-
tion therapy provided by a registered dietitian over a period of 6 weeks to 6 months can
result in substantial changes in dietary habits. The first visit length is usually 45–90 min
and subsequent visits should last between 30 and 60 min.
4. NUTRIENTS AND CVD
4.1. Fat
Reducing the total amount of fat in the diet has long been a method for decreasing the
risk of CHD. Early studies also suggested that the type of fat might be more important
than the total amount of fat in the diet. Two secondary prevention trials testing total
fat reduction failed to find a significant reduction in serum cholesterol or CHD events
(10,11). Data from the largest analysis done in this area indicate that types of fats may
play a more important role in CHD risk than total fat intake. The Nurses’ Health Study
revealed that higher intakes of TFA and, to a smaller extent SFA, are associated with
increased risk. In contrast, higher intakes of nonhydrogenated polyunsaturated (PUFA)
and monounsaturated fatty acids (MUFA) correlate with decreased risk (12).
As shown in Table 3, total fat intake can cover up to 35% of total daily calories, as
long as it comes mainly from MUFA. SFA should be limited to <7% of energy, TFA
to <1% of energy, and dietary cholesterol to <200 mg/day. Evidence for the benefits of
lowering dietary SFA was provided by the Seven Countries Study (13) in which regional
differences in death from CHD were strongly correlated with SFA intake. Many popula-
tion studies have since then provided evidence of associations between diets high in SFA
and increased total cholesterol and LDL-C levels, as well as increased risk of both CHD
and CVD (14). When SFA were replaced by unsaturated fats, total plasma cholesterol
was lowered (15). Moreover, substituting PUFA for SFA does appear to be beneficial in
lowering serum cholesterol and reducing cardiovascular mortality, as demonstrated by
the Finnish Mental hospital Study, the Los Angeles Veteran Study, the Oslo Diet-Heart
Study, and the MRC study (1).
A recent study, known as The Omniheart Randomized Trial, evaluated the effects of
three reduced SFA and dietary cholesterol diets that varied only in macronutrient content
(16). All three of the diets provided 6% of energy from SFA. Both the carbohydrate-
rich and protein-rich diets provided 27% energy from total fat, although the content
of the carbohydrate and protein varied. The carbohydrate-rich diet consisted of 58%
from carbohydrate, whereas the protein-rich diet provided 25% of energy from protein.
The third diet, the unsaturated fatty acid-rich diet, was higher in fat, providing 37% of
energy from total fat (21% of which was MUFA). Both the protein and the unsaturated
fatty acids-rich diet improved triglyceride levels statistically. The unsaturated fatty acids
diet also improved high-density lipoprotein cholesterol (HDL-C) levels. These results
suggest that partial substitution of carbohydrate for protein or unsaturated fatty acids
226 Kontogianni et al.
can favorably affect both blood triglycerides and HDL-C. Data from the Nurses Health
Study also suggest that the highest (5.7 g/day) vs. the lowest (2.4 g/day) quintile of TFA
intake is associated with an increase in CHD risk (17). Other studies continue to emerge
that further bolster the argument to avoid trans fatty acids (14).
The most commonly occurring MUFA in the diet is oleic acid (C18:1), which is abun-
dant in olive and canola oils as well as in nuts. There has been continued debate over the
past several years on whether MUFA or PUFA should replace SFA in the diet. The early
metabolic studies by Mattson and Grundy (18) revealed that MUFA lowered LDL-C concen-
trations with no effect on HDL-C levels, whereas PUFA lowered both LDL-C and HDL-C
levels. Subsequent studies, even including metaanalyses, have suggested that the effects
of MUFA and PUFA on plasma lipoprotein profiles are similar (15). Moreover, dietary fat
may influence the risk of CHD by altering the susceptibility of lipoproteins to oxidation.
Previous work has shown that, in the test tube, LDL-C particles enriched in MUFA are less
susceptible to oxidation than particles enriched in n-6 PUFA (19). These results have also
been supported by a study that examined the oxidation of LDL-C from subjects consuming
diets enriched in olive oil (MUFA), rapeseed oil (MUFA plus n-3 PUFA), or sunflower
oil (n-6 PUFA) (20). LDL-C oxidation was lowest in the olive oil group, intermediate in
the rapeseed oil group, and highest in the sunflower oil group. This indicated that MUFA
reduced LDL-C oxidation compared with n-6 PUFA. Also, when comparing MUFA and
PUFA, it may be important to distinguish between n-6 and n-3 PUFA. The potential health
benefits of n-3 PUFA are being presented in the supplements section.
Finally, epidemiological evidence and intervention studies clearly show that in humans
SFA significantly worsen insulin-resistance, while MUFA and PUFA improve it through
modifications of the composition of cell membranes. Shifting from SFA to MUFA in-
take can also affect blood pressure significantly, especially by reducing diastolic blood
pressure (21).
Therefore, on the basis of current evidence, emanating mainly from observational
studies, patients should be encouraged to focus on replacing the main sources of SFA and
TFA. SFA are generally found in animal fats in foods such as meat and dairy. TFA are
generally produced by hydrogenation of vegetable oils and found in food items such as
bakery goods or fried foods. These foods should be replaced with foods high in MUFA
and PUFA, such as olive oil, nuts, seeds, and fish.
4.2. Protein
Protein does not directly affect serum LDL-C levels or other lipid profile compo-
nents. By encouraging patients to replace some of their animal protein sources with
plant-based protein sources however, dietitians can indirectly address intake of total
dietary fat, particularly in the form of saturated fat. Plant sources of protein include
vegetables, legumes, whole-grains, and nuts. In addition, patients should be educated on
correct portion sizes of protein rich foods.
4.2.1. Soy Protein
Epidemiological evidence from human subjects suggests that high soybean consump-
tion, the main dietary source of isoflavones, may be cardioprotective. Existing data sug-
gest that soybean food and soybean protein interventions may have a beneficial effect on
Chapter 12 / Nutrition Recommendations and Interventions 227
certain aspects of the lipoprotein profile, while there is limited data to support a lipid-
lowering effect of isoflavone extracts. Available evidence in this area remains minimal
however, and, at this time, the only potential link that has been suggested is between soy
consumption and lowered LDL-C. No data have shown substantial benefits of soy protein
consumption on HDL-C, total cholesterol, triglycerides, or lipoprotein(a). Data from in
vitro and animal experiments are currently emerging and suggest that isoflavones may
be cardioprotective by mechanisms independent of blood lipids, but these underlying
mechanisms remain only partly understood. As a result, more recent research efforts have
focused on the potential effects of phyto-oestrogens on blood pressure, in vivo measures of
vascular function, such as flow-mediated dilation and novel biomarkers of CHD risk (i.e.,
inflammatory factors, coagulation, and fibrinolytic factors as well as markers of LDL-C
oxidation). To date these studies have not been systematically reviewed. Data from human
studies on the effects of soybean foods and soybean protein on blood pressure are equivo-
cal, but it is clear that there is no evidence for an effect of isoflavone extracts on blood
pressure. Moreover, although there is growing interest in the potential direct effects of iso-
flavones on the arterial wall, the available data from human studies are inconclusive (22).
Consumers should be advised that, although FDA issued a health claim in 1999 stat-
ing that 25 g/day soy protein was associated with reduced risk of CHD, the current body
of research in this area does not appear to fully support this claim. Soy products such
as tofu, soy butter, soy nuts, or some soy burgers may be beneficial to cardiovascular
and overall health because of their high content of PUFA, fiber, vitamins, and minerals
and low content of SFA. Therefore, using these and other soy foods to replace foods
high in animal protein that contain saturated fat and cholesterol may confer benefits to
cardiovascular health (23).
4.3. Carbohydrates
The relationship of carbohydrate dietary intake with CHD appears to be mediated by
several, mainly indirect, mechanisms: contribution to total energy intake and effect on
overweight and obesity, influence on central obesity, effects on plasma lipids (especially
triglycerides), and effects on glycemic control. The balance between carbohydrates and
fat as sources of energy as well as the fiber component of the diet are also areas of inter-
est. In feeding experiments, an increase in dietary energy from carbohydrates is usually
associated with a moderate increase in fasting plasma triglyceride levels in the first few
weeks, but these return to near baseline levels in the following weeks (24).
The effect of a high-carbohydrate diet on HDL-C and thereby on the total to HDL
cholesterol ratio, as well as on the particle size of LDL-C, are matters of scientific inter-
est as is the influence on vascular function and subsequent risk of CHD. Diets high in
carbohydrates appear to reduce HDL-C levels and increase the fraction of small dense
LDL-C, both of which may adversely impact vascular disease. This dyslipidemic pattern is
consistent with the elevation of plasma triglycerides. Currently, there is no clear evidence
that the risk of CHD is independently altered by carbohydrate levels in the diet (25). On
the contrary, postprandial hyperglycemia is increasingly recognized as an independent
risk factor for cardiovascular disease. Glycemic “spikes” may adversely affect vascular
structure and function via multiple mechanisms, including (acutely and/or chronically)
oxidative stress, inflammation, low-density lipoprotein oxidation, protein glycation, and
228 Kontogianni et al.
procoagulant activity. The glycemic index of foods might also be a determinant of the
extent to which carbohydrates can influence the glycemic status. Low glycemic index
diets in hyperlipidemic and type 2 diabetic subjects have been associated with significant
reductions in LDL-C and triglycerides with no effect on HDL-C levels (26,27).
In attempting to follow a low-fat diet, many patients erroneously substitute carbohy-
drates for SFA. Although this does generally reduce overall caloric intake, it does not
effectively reduce cardiovascular risk. In fact, it can even exacerbate related metabolic
risk factors, including insulin resistance, unless careful choices of low glycemic index
foods are made.
4.4. Fiber
A diet that provides 25–30 g (or 10–13 g/1,000 Kcal) of total dietary fiber, including
at least 7–13 g of soluble fiber, is a well tolerated and effective way to decrease lipid
levels and CHD risk (14). Foods rich in soluble fiber include oatmeal, oat bran, bar-
ley, fruits with skins intact, eggplant, Brussels sprouts, and ground flaxseed. Moreover,
beans and legumes (such as black-eyed, soy, and kidney beans) are particularly good
sources of fiber. Soluble fiber binds to LDL-C and carries it out of the body, improving
the patient’s overall lipid profile.
High fiber diets are also associated with other health benefits including improved glycemic
control and reduced body weight due to increased satiety. Patients must be educated in read-
ing food labels in order to better identify truly whole grains. The first ingredient reported
on the labels must be a whole grain such as wheat, oats, or barley. Likewise, breads must
list the first ingredient as “whole grain flour.”
4.5. Alcohol
Several studies indicate that moderate drinking is associated with a decreased risk of
CHD (28) but the exact mechanisms underlying risk reduction due to moderate alcohol
consumption remain largely unknown. The beneficial effects of alcohol could be due to
an increase in HDL-C cholesterol and apo A-1 and/or a modest improvement in hemo-
static factors (29). Alcohol may also be associated with lower LDL-C levels, but it is
unclear whether this is independent of other dietary factors. A subset of heavier drinkers
demonstrates a substantial increase in triglyceride levels, but this is infrequently seen
with light/moderate drinking. Moreover, antithrombotic actions of alcohol could par-
tially account for the lower CHD risk at very light drinking levels (e.g., several drinks
per week) observed in several epidemiologic studies. During the last few years, both
epidemiological and experimental studies have supported the hypothesis that, in addition
to ethanol, certain substances in wine (especially red wine) have cardioprotective effects.
The best studied of these substances are polyphenols, categorized as flavonoids [mainly
flavonols (quercetin and myricetin), flavanols or flavan-3-ols (catechin and epicatechin),
and the anthocyannins] and nonflavonoids [including the stilbenes (resveratrol), hydrox-
ynnamates (caffeic, caftaric, and coutaric acids), and the hydroxybenzoates] (30). Data
suggest that ingestion of grape flavonoids is followed by a reduction in platelet activa-
tion (31), inflammation and low-density lipoprotein oxidation (32), improvement of
endothelial function due to induction of nitric oxide release with the subsequent effect
of vasorelaxation (33) and elevation in HDL-C levels (34), but these data need to be
confirmed and expanded.
Chapter 12 / Nutrition Recommendations and Interventions 229
It has been observed that the lipimic profile differs, among drinkers of different spirits,
with wine drinkers having the most favorable CHD risk profile. Differences in drinking
patterns among subjects consuming different beverage types could also play a role in
terms of their effects on CHD risk factors. The question of whether the different risks
and benefits associated with the different types of alcoholic beverages – beer, wine, and
spirits – is still unresolved, but it seems likely that ethyl alcohol is one of the major
factors lowering CHD risk (35).
It has been shown in both the US National Alcohol Survey and a Finnish study that
light to moderate drinkers who experienced occasional bouts of heavy drinking had a
significantly higher mortality rate compared with those who had the same average intake
(36,37). A recent large study from Denmark also showed that, for the same average intake,
binge drinkers had a higher all-cause mortality than steady drinkers (38). Moreover, in
a study of 11,511 cases of acute myocardial infarction or fatal CHD and 6,077 controls
in New South Wales, Australia, it was shown that individuals who had a steady small
intake of alcohol had lower odds for fatal CHD while those who had the same average
intake, but consumed their alcohol once or twice per week, did not (39). In the Health
Professionals study, Mukamal et al. recently showed that cardioprotection seemed to
be more strongly related to the frequency of intake rather than to the amount of alcohol
ingested (40). This study has very recently been followed by a more detailed description
of the mediators of the effect of drinking pattern, namely HDL-C, hemoglobin A1c and
fibrinogen, as responsible for 75–100% of the association observed (41). In conclusion,
these findings strongly suggest that drinking pattern – steady vs. binge drinking – plays
a role in the apparent cardioprotective effect of alcohol. Finally, recent reports suggest
that drinking during a meal, in a true Mediterranean diet pattern, is beneficial for both
CHD and hypertension, while alcohol taken in between meals does not show any sub-
stantial benefit (42,43).
Moderate drinking is defined as no more than one drink per day for women and no more
than two drinks per day for men, ideally consumed with meals. A 12-ounce bottle of beer,
a 4-ounce glass of wine, and a 1½ shot of 80-proof spirits all contain the same amount of
alcohol (one half ounce) (2). People who do not habitually consume alcohol are not advised
to incorporate alcoholic drinks into their diets in order to reduce their CHD risk, and indi-
viduals who consume alcohol are advised to do so in moderation, as heavy consumption
is associated with an increase in the prevalence of the metabolic syndrome, type 2 diabetes
mellitus, stroke, peripheral arterial disease, and overall CHD (44). It is also important for
patients to remember to limit their intake of alcohol within a reasonable range to prevent
weight gain, as alcohol supplies calories with limited nutritional benefits.
5. FOOD GROUPS AND CVD
5.1. Fruits and Vegetables
Although there has been a consensus that fruits and vegetables should be consid-
ered as cornerstones in a heart healthy diet, it is only recently that solid epidemiologi-
cal evidence has linked these two food groups together. The largest relevant study has
reported a significant inverse association between consumption of fruits and vegetables,
particularly green leafy vegetables and vitamin C-rich fruits and vegetables, and risk of
230 Kontogianni et al.
CHD (45). Every single serving per day of fruits and vegetables was associated with a
4% decrease in CHD risk. It is still unclear whether the fruits and vegetables themselves
have cardioprotective features, or whether they simply displace from the diet other foods
with harmful properties. Two examples of diet patterns that are consistent with the AHA
guideline to increase fruits and vegetables are the DASH Diet and the TLC (Therapeutic
Lifestyle Changes) Diet. Both recommend consumption of at least 8–10 servings of
fruits and vegetables combined per day (2). However, the biologic mechanisms whereby
fruits and vegetables may exert their beneficial effects are not entirely clear and are
likely to be numerous. Several nutrients and phytochemicals, including fiber, potassium,
folate, lycopene, and polyphenols, could be independently or jointly responsible for the
apparent reduction in CHD risk. Functional aspects of fruits and vegetables, such as
their low dietary glycemic load and low energy density, may also play a significant role.
Moreover, fruit and vegetable consumption has been positively associated with total
adiponectin levels, an adipocytokine that has been shown to improve insulin action as
well as glucose and lipid metabolism (46). Additionally, consumption of fruits has been
positively associated with high molecular weight adiponectin, the fraction of adiponec-
tin that has been proposed to be more closely associated with insulin resistance and the
presence of metabolic syndrome (47). Although it is important to continue our quest for
mechanistic insights, given the great potential shown in epidemiology studies, increased
fruit and vegetable intake is recommended (48). A variety of deep colored fruits and
vegetables is recommended because of their high micronutrient content. Moreover, due
to their significant nutrient density and fiber content, fruits and vegetables at the com-
mencement and in between meals may play a role in inducing satiety, which would in
turn reduce calorie intake and promote weight loss.
5.2. Whole Grains
Several epidemiological studies have reported that whole-grain intake is protective
against CVD, diabetes, and obesity. Whole grains are concentrated sources of dietary
fiber, resistant starch, and oligosaccharides, i.e. carbohydrates that escape digestion
in the small intestine and are fermented in the gut, producing short chain fatty acids.
Short-chain fatty acids lower colonic pH, serve as an energy source for the colonocytes,
and may alter blood lipids. Moreover, whole grains are rich in antioxidants, including
trace minerals and phenolic compounds, which have been linked to disease prevention.
Finally, whole grains mediate insulin and glucose responses and also contain many other
compounds, such as phytates, phyto-oestrogens (e.g., lignans), plant sterols/stanols,
vitamins, and minerals that may protect against chronic diseases (49). Recently, intake
of whole grains has been associated with higher adiponectin levels. In a cross-sectional
study of 220 apparently healthy adult Mediterranean women, it has been shown that
adherence to a dietary pattern characterized by high intake of whole-grain cereals and
low-fat dairy products, as well as low intake of refined cereals, was significantly and
positively associated with adiponectin levels after controlling for potential confound-
ers (50). Moreover, intake of whole grains was associated with a reduced incidence of
fatal and nonfatal CHD in many large prospective population studies (51). These studies
suggest a 20–30% reduced risk of CHD in persons with a daily intake of ³3 servings of
whole-grain food items.
Chapter 12 / Nutrition Recommendations and Interventions 231
Several RCTs examining the effect of whole grain consumption on CHD risk factors,
such as blood lipids, hypertension, and insulin resistance, as well as on body weight
and inflammatory markers, are currently in progress. Current guidelines for whole grain
intake emanate mainly from epidemiological studies that cannot prove causality. The
recommended amount of grain servings per day is 6–8 and the AHA recommends that
at least half of these should come from whole grain sources (2). Servings size examples
include one slice of wholemeal bread, 1 oz dry wholegrain cereal, and half cup cooked
brown rice, wholegrain pasta or cereal.
5.3. Nuts
Nuts, which are naturally high in MUFA and PUFA, have been associated with LDL-C
lowering effects and an overall improvement in lipid profiles (52). The species studied
so far include walnuts, almonds, legume peanuts, macadamia nuts, pecans, and pista-
chio nuts. Collectively, clinical studies indicate that inclusion of nuts in a lipid-lowering
diet has favorable effects, especially on LDL-C levels; however, existing studies do not
provide unequivocal evidence of an additive effect of nuts to the effects of a low SFA
diet per se. The fatty acid profile of nuts (high in unsaturated fatty acids and low in
saturated fatty acids) lowers blood cholesterol by altering the fatty acid composition of
the diet as a whole. Nuts are also a rich source of dietary fiber and micronutrients, such
as phytosterols, arginine, potassium, copper, magnesium, selenium, and vitamin E (25).
Frequent nut and seed consumption has been associated with lower levels of inflamma-
tory markers (namely C-reactive protein and interleukin-6), lower levels of fibrinogen,
and lower blood pressure (provided that they are unsalted) (53,54).
It must, however, be recognized that the high-fat content of nuts makes them high in
calories too. Advice to include nuts in the diet must be tempered in accordance with the
desired energy balance. Although further research is needed to characterize the independ-
ent protective effects of these food items against CHD and to identify the mechanisms
of such protection, available evidence suggests that nuts should be recommended as
part of an energy appropriate healthy diet, which is intended to reduce the risk of CHD.
Federal guidelines recommend nut consumption in ¼ cup daily or up to 5 oz per week
(55). Patients should be encouraged to focus on isocalorically substituting nuts for other
foods in their diet to prevent excess calorie intake and subsequent weight gain.
5.4. Dairy Products
Dairy products, especially milk, have been considered as potential promoters of CHD
because they are sources of cholesterol and SFA but the short-chain fatty acids and the
long-chain stearic acid, which do not adversely affect cholesterol levels, are consider-
able parts of the SFA in milk fat. Milk intake is probably positively related to blood lipid
levels, but the effect shown in many studies is either trivial or absent. In fact, milk sup-
plementation led to a decrease in blood lipids in some studies, and it has also been sug-
gested that milk and milk products may contain antiatherogenic bioactive substances to
negate the effects of SFA and cholesterol (56). There is also growing evidence support-
ing a protective role of dairy consumption (especially low-fat); for example an inverse
relationship has been observed between consumption of dairy products and the odds
of having acute coronary syndrome (57). A dietary pattern that highlights the possible
protective role of low-fat dairy products is the DASH diet. The DASH dietary pattern
232 Kontogianni et al.
emphasizes fruits, vegetables, and low-fat dairy products and is reduced in saturated and
total fats and cholesterol. This diet has been shown to lower blood pressure in men and
women, those with or without hypertension, those who are young or old, and in African
Americans and non-African Americans (58).
Calcium, bioactive peptides, and several as of yet unidentified components in whole
milk may protect from hypertension. Folic acid, vitamins B6 and B12 as well as other
components may contribute to low homocysteine levels, while conjugated linoleic acid
may have hypolipidemic and antioxidative (and thus antiatherogenic) effects (59). Ad-
ditionally, hypocholesterolemic or hypotensive properties have been attributed to fer-
mented dairy products (e.g., yogurt), although the existing data do not allow for definitive
conclusions. It has also been proposed that different bacterial strains in fermented milk
products have different cholesterol-reducing properties. Still, apparently a necessary
condition is that the bacteria, called probiotic bacteria, are able to survive the gut and
colonize the intestine (60). These data need to be confirmed by future studies.
6. WHOLE DIET APPROACH AND CVD
Although much of the research to date has focused on individual nutrients and their
effect on CHD, broader research is now investigating the impact of diet as a whole.
People consume meals consisting of several food items containing a broad combina-
tion of nutrients. Therefore, complicated or cumulative intercorrelations and interac-
tions between nutrients and food groups should be studied. Rather than assessing single
nutrients, foods, or food groups, it has been suggested that a holistic dietary approach,
which examines the effect of dietary patterns in terms of chronic disease prevention and
treatment, may be a more valuable approach to evaluate associations between diet and
biological markers and/or disease outcomes (3).
6.1. “Prudent” vs. “Western” Dietary Patterns
The methodology for defining dietary patterns consists of three main approaches:
analysis of dietary indices, cluster analysis, and factor analysis. The last two approaches
often reveal a “prudent” dietary pattern, mainly characterized by higher intakes of fruits,
vegetables, legumes, fish, poultry, and whole grains, and a “Western” dietary pattern,
characterized by higher intakes of red and processed meats, sweets/desserts, French
fries, and refined grains. Adherence to the “prudent” dietary pattern has been associ-
ated with significantly lower relative risks for CHD after adjustment for several factors
known to affect CHD risk in men. Those at the highest quintile of adherence showed
a 30% lower risk (61). The respective effect in women was 24% lower relative risk for
CHD (62). Moreover, in the Health Professionals Follow-up Study, significant positive
correlations between a “Western” dietary pattern and blood insulin, C-peptide, leptin,
and homocysteine concentrations were observed. An inverse correlation with plasma
folate concentrations was also noted. The “prudent” dietary pattern was positively cor-
related with plasma folate and inversely correlated with insulin and homocysteine con-
centrations (63). Adherence to the “prudent” pattern has also been inversely associated
with plasma concentrations of CRP and E-selectin, after adjustment for age, body mass
index, physical activity, smoking status, and alcohol consumption (64), as well as with
lower risk for type II diabetes both in women (65) and men (66), with enhanced insulin
sensitivity (67) and with stroke prevention (68).
Chapter 12 / Nutrition Recommendations and Interventions 233
6.2. Mediterranean Diet
The term “Mediterranean diet” has been widely used to describe the traditional die-
tary habits of people in Crete, South Italy, and other Mediterranean countries during the
1960s. It is schematically depicted as a food pyramid. This dietary pattern is character-
ized by plentiful plant foods (fruits, vegetables, breads, other forms of cereals, beans,
nuts, and seeds), olive oil as the principal source of fat, moderate amounts of dairy prod-
ucts (mainly cheese and yogurt), low to moderate amounts of fish and poultry, red meat
in low amounts and wine consumed in low to moderate quantities, usually with meals
(69). There are several beneficial nutrients that are abundant in the Mediterranean diet,
such as MUFA, a balanced ratio of omega-6/omega-3 essential fatty acids, high amounts
of fiber, antioxidants such as vitamins E and C, resveratrol, polyphenols, selenium,
glutathione, and many others that are currently under investigation.
In a recent systematic review, Serra-Majem et al. reviewed and analyzed the experi-
mental studies on Mediterranean diet and disease prevention (70). Most of the clinical
trials exploring the effect of Mediterranean diet on lipids levels found reductions in total
and low-density lipoprotein cholesterol (LDL-C), triglycerides, apolipoprotein B, and
very-low-density lipoprotein cholesterol, and an increase in HDL cholesterol. A decrease
in the number of small LDL-C particles has also been observed in some studies. En-
dothelial function improved with the adoption of the Mediterranean diet, and endothelial
dependent vasodilatation was increased by adding nuts to the Mediterranean diet. Insulin
resistance and metabolic syndrome were reduced after shifting to a Mediterranean diet,
but some studies showed no effects on insulin or glucose levels. Importantly, studies
addressing secondary prevention of cardiovascular disease have shown a significantly
reduced odds ratio for fatal myocardial infarction (between 0.25 and 0.7).
More specifically the results of three studies examining the effects of Mediterranean
diet in the secondary prevention of CHD are of great interest. The Indo-Mediterranean
diet Heart Study explored the cardioprotective effects of a Mediterranean style diet rich
in a-linolenic acid vs. a Step I National Cholesterol Education Program (NCEP) prudent
diet in 1,000 patients with angina pectoris, myocardial infarction, or surrogate risk factors
for CHD (71). Total cardiac end points were significantly fewer in the Mediterranean diet
group compared with controls. Sudden cardiac deaths and nonfatal myocardial infarctions
were also reduced. The investigators noted that in the Mediterranean diet group, patients
with preexisting CHD had significantly greater benefits compared with such patients in
the control group and concluded that an Indo-Mediterranean diet, rich in a-linolenic acid,
might be more effective in primary and secondary prevention of CHD than the conventional
step I NCEP prudent diet. Moreover, the Lyon Diet Heart Study, a randomized secondary
prevention trial aimed at testing whether a Mediterranean-type diet may reduce the rate
of recurrence after an initial myocardial infarction (72), focused on cardiac death and
nonfatal myocardial infarction, unstable angina, stroke, heart failure, and pulmonary or
peripheral embolism. In the Mediterranean diet group, all the above-mentioned outcomes
were significantly reduced compared with a prudent Western-type diet group during the
4 years of follow-up after the first infarction. Finally, the GISSI-Prevenzione clinical trial
explored whether simple dietary advice to increase the consumption of Mediterranean
foods, given in a clinical setting, leads to reduced mortality after a myocardial infarction
(73). When the range of observed scores of adherence to the Mediterranean-like dietary
pattern was split into equal quartiles, the chance of death was decreased by 31%, 34%, and
49% for the second, third, and fourth quartiles, each compared with the first (depicting
234 Kontogianni et al.
the least adherence), after adjustment for nondietary confounding variables. Overall, a
10% (one unit) increase in the dietary score reduced the risk of mortality by 15%. It has
been concluded that patients with myocardial infarction can respond positively to simple
dietary advice, and this can be expected to lead to a substantial reduction in the risk of
early death. Regardless of any drug treatment prescribed, clinicians should routinely
advise patients with myocardial infarction to increase the frequency of consumption of
foods belonging to what is perceived as “Mediterranean diet.”
6.3. DASH Diets
Dietary strategies to lower blood pressure play an important role in reducing overall
CHD risk. The most well known controlled feeding study to test the dietary affects on
hypertension is known as DASH (74). The results of the study clearly show that a diet high
in fruits, vegetables, and low-fat dairy products, but low in saturated and total fat, reduces
blood pressure in hypertensive and normotensive individuals (more so than the control
diet). The composition of the DASH diet is 27% calories from total fat, 6% calories from
SFA, 18% calories from protein, 55% calories from carbohydrate, 150 mg cholesterol and
two levels of sodium intake − 2,400 or 1,500 mg. The calcium, magnesium and fiber con-
tent of the diet also stand out as high when compared with the typical American diet, with
1,250 mg calcium, 4,700 mg potassium, and 30 g fiber. The DASH diet was demonstrated
to be effective as first-line therapy in individuals with stage I isolated systolic hyperten-
sion (i.e., with a systolic blood pressure of 140–159 mmHg and a diastolic blood pressure
below 90 mmHg), with 78% of the persons on the DASH diet reducing their systolic blood
pressure to <140 mmHg, in comparison to 24% in the control group (75). DASH has also
be proven to be effective in lowering plasma levels of total and LDL-C but these changes
were also accompanied by a reduction in HDL-C levels. While the Framingham risk score
improved as a result of the impact on total and LDL-C as well as on blood pressure, the
impact of the associated reduction in HDL-C needs to be assessed (76).
Furthermore, the PREMIER trial evaluated the effects of simultaneously implementing
the DASH diet and established lifestyle recommendations for hypertension (weight loss,
sodium reduction, increased physical activity, and limited alcohol intake) in free-living
individuals. Participants in both intervention groups (established guidelines plus DASH
vs. established guidelines) lost weight and reduced dietary sodium and fat intakes dur-
ing the 18 months. In the established plus DASH group, participants made additional
dietary changes, significantly increasing their intakes of fruits, vegetables, and dairy
products and further reducing their intake of saturated and total fats. As a consequence,
their hypertension status improved (77).
7. SUPPLEMENTS
7.1. Omega-3 Fatty Acids and Fish Oils
Fish oil, rich in omega-3 PUFA, is thought to contribute to the prevention or alleviation
of many illnesses, though the most established benefits associated with fish oil are
cardioprotective. Beneficial effects associated with fish oil include ameliorating
arrhythmia, lowering serum triglycerides, decreasing thrombosis and inflammation,
and improving endothelial function (78–80). The active ingredients are thought to be
the long chain docosahexaenoic acids (DHA) and eicosapentaenoic acids (EPA). DHA
Chapter 12 / Nutrition Recommendations and Interventions 235
and EPA rich oils are found in fatty fish such as salmon, mackerel, lake trout, her-
ring, sardines, and albacore tuna. Currently, the AHA recommends consuming fatty
fish at least twice a week (~8 oz per week). Eating more servings of fish per week is
beneficial, but some fish, particularly tuna, may contain high amounts of contaminants
such as methyl mercury. Sensitive subgroups of the population, primarily children and
pregnant women, are advised by the FDA to avoid eating those fish with the potential
for the highest level of mercury contamination (e.g., shark, swordfish, king mackerel,
or tilefish), eat up to 12 oz (two average meals) per week of a variety of fish and shell-
fish that are lower in mercury (e.g., canned light tuna, salmon, pollock, catfish), and
check local advisories about the safety of fish caught by family and friends in local
lakes, rivers, and coastal areas (81). For those who are already diagnosed with heart
disease, the AHA recommends taking 1,000 mg a day of DHA plus EPA from fish oil,
preferably from fatty fish, but supplements can augment the amount taken in the diet
and should be taken under the supervision of a doctor. Supplementation of 2,000–4,000
mg of DHA and EPA may also be beneficial for those who have hypertriglyceridemia
(82). The FDA does not recommend taking more than 3,000 mg without consulting a
physician due to risks that include bleeding associated with these supplements (see also
chapter on hyperlipidemia).
a-Linolenic acid (ALA) is another form of omega-3 fatty acid derived from plant
sources such as soybeans, flaxseed, and walnuts. ALA is a precursor molecule to EPA
and DHA, and requires several metabolic steps before it can exert comparable benefits.
Only 5–15% of ALA is converted into more active compounds, however, making it
overall a less attractive source of long chain polyunsaturated fats. Trials, like the Lyon
Diet Heart Study, which showed that ALA consumption in the context of a Mediter-
ranean diet reduced total and cardiovascular mortality as well as nonfatal myocardial
infraction, support the use of ALA and fish oil in the secondary prevention of CHD (1).
However, at present, the body of research concerning the cardioprotective benefits of
ALA is not conclusive.
7.2. Plant Sterols/Stanols
Plant sterols (b-sitosterol, campesterol, and stigmasterol) and their saturated deriva-
tives, the stanols (sitostanol and campestanol), are the naturally occurring equivalents
of the mammalian sterol cholesterol. Edible oils, seeds, and nuts have a high content
of plant sterols. The Western diet contains about 100–300 mg/day of plant sterols and
20–50 mg/day of plant stanols (83). Because of their structural similarity to cholesterol,
plant sterols and stanols can replace cholesterol in the human body; they decrease total
cholesterol and LDL-C levels by reducing dietary and biliary cholesterol absorption via
the displacement of cholesterol from micelles in the intestine. Plant sterols and stanols
have been shown to lower LDL-C by 10–14% (84,85), but they do not alter HDL-C or
triglyceride levels (86).
Available data indicate that the maximum effect of stanols/sterols is seen at an intake
of at least 2 g/day (2) taken on a daily basis. In addition to plant sterol/stanol supplements,
generally available in a soft gel capsule form, many products, including margarines, dairy
products, cereals/cereal bars and beverages, now include stanols/sterols and are available
in grocery stores. As with nuts, patients should be encouraged to substitute these foods for
other isocaloric foods in their diet to prevent excess calorie intake and subsequent weight
236 Kontogianni et al.
gain. Plant stanols/sterols are generally well tolerated with no adverse events. Some research
indicates, however, that a decline in serum carotenoid and fat soluble vitamins levels may
be brought on by consuming stanols/sterols (87). Thus, patients should be encouraged to
consume foods that are high in carotenoids, including fruits and vegetables with deep colors
of red, yellow, orange and green, such as carrots, kale, collard greens, tomatoes, sweet
potatoes, peaches, and apricots.
7.3. Antioxidant Supplements and B Vitamins
Oxidative stress is a putative cause of atherosclerotic disease. Therefore, research has
been directed toward the potential role of antioxidants in reducing CHD risk (9). At this
time, however, there have been no clinical trials to strongly support the cardioprotective
effects of antioxidants. Reports of the positive effects of antioxidants from foods and sup-
plements on CHD have arisen from observational studies only. The most extensively stud-
ied antioxidants are vitamin C, E, b-carotene, coenzyme Q10, bioflavanoids, and selenium.
For the time being, patients should not be encouraged to take in high levels of antioxidants
in the form of supplements, due to available evidence from trials that they may, in fact,
do more harm than good. b-Carotene supplementation has been associated with increased
risk of lung cancer in smokers (88), whereas long-term vitamin E supplementation has
been associated with increased risk for heart failure in patients with vascular disease or
diabetes mellitus (89). Furthermore, a metaanalysis concluded that high doses of vitamin
E may increase total mortality (90). It is therefore recommended that patients simply try
to include in their diet more food sources of antioxidants, such as fruits, vegetables, and
whole grains. Although antioxidant vitamins may theoretically be beneficial for reduc-
ing the risk of CHD, more conclusive data from large controlled clinical trials are clearly
needed.
The current body of research on folate and other vitamins of the B complex is similarly
inconclusive. There has been strong evidence showing a correlation between elevated
homocysteine levels and CVD risk (91), but there is insufficient evidence to suggest
that supplementation with folic acid, B6, and B12 plays an important role in reduction
of CVD risk. More research is necessary in this area before supplementation of these
vitamins is recommended for CVD risk reduction.
8. ACHIEVING A HEALTHY BODY WEIGHT
Obesity is clearly a risk factor for CHD and has been consistently shown to influence
several CHD factors, namely blood LDL-C, triglyceride, and HDL-C levels, hyperten-
sion, and insulin resistance (92). Weight gain prevention is obviously the most desirable
method for avoiding the excess risk of CHD associated with obesity, but for the majority of
CHD patients, weight gain has already occurred and weight reduction and/or maintenance
becomes the greatest obstacle. For patients who are already overweight or obese, the initial
goal of weight loss therapy is to reduce body weight by ~10% from baseline. If this goal
is achieved, further weight loss can be attempted, as indicated through further evaluation.
A reasonable time line for a 10% reduction in body weight is 6 months. For overweight
patients with BMIs in the typical range of 25–35 kg/m2, a decrease of 300–500 kcal/day
will result in weight loss of about 0.5–1 lb/week and a 10% loss in 6 months. For more
severely obese patients with BMIs > 35 kg/m2, deficits of about 500–1,000 kcal/day will
Chapter 12 / Nutrition Recommendations and Interventions 237
lead to weight loss of ~1–2 lbs/week and a 10% weight loss in 6 months (7). Definitions
of success for a weight management program are patient-specific. Reduction of risk fac-
tors, even if weight is not lost, is considered “success” from a health point of view. For
patients unable to achieve significant weight reduction, prevention of further weight gain
is an important goal; such patients may also be encouraged to participate in a weight man-
agement program. For patients resistant to weight reduction through dietary intervention
alone, a concomitant pharmacotherapy and physical activity program may help to achieve
the weight loss target, as indicated (see Chap. 16).
9. PHYSICAL ACTIVITY
Observational and randomized controlled clinical studies consistently show that
physical activity is effective in both primary and secondary prevention of CHD. The
effects of physical activity on CHD risk reduction are due, in part, to favorable effects on
blood pressure, triglyceride levels, HDL-C levels, insulin sensitivity, glucose tolerance,
and body weight. Physical activity and weight loss decrease LDL-C levels and lessen the
reduction in HDL-C that often occurs with a diet that is low in total fat and SFA (93).
The American College of Sports Medicine and the American Heart Association
recommend that people should get a minimum of 30 min of moderate-intensity aerobic
physical activity for 5 days each week or a minimum of 20 min of vigorous-intensity
aerobic activity for 3 days each week (94). Moderate physical activity is described as
walking, climbing stairs, gardening, yard work, moderate-to-heavy housework, dancing,
and exercise at home. Patients who stress that they are unable to find time for daily activity
should be encouraged to accumulate exercise minutes in shorter bouts of 10 min at a time
throughout the day to reach their 30 min goal. Although existing research evidence is
not conclusive, a summary of the experimental findings suggests that moderate-intensity
physical activity in shorter bouts (usually lasting 10 min) that is accumulated toward the
30-min minimum can be as effective as single, longer exercise sessions in reducing risk
factors for chronic disease (94). In patients with cardiovascular risk factors, individually
tailored prescriptions must take into account the patient’s main metabolic defect. To
modify the lipid profile, exercise should be aerobic and of moderate intensity, with an
energy expenditure greater than 300 kcal (equivalent to a weekly energy expenditure of
at least 2,000 kcal). With regard to insulin sensitivity, power training is just as effective
as aerobic exercise, and if the prime objective is to lose weight, prolonged, mild-intensity
work should be performed daily if possible (95).
Moreover, special care must be taken during the assessment of patients with chronic
disease. Once the patient has been stabilized after an acute coronary event, physical ac-
tivity, along with psychological support, educational and preventive strategies, should be
included in rehabilitative therapy. It has been shown that to improve cardiovascular adapt-
ability to effort, the intensity of physical exercise must be 60–75% VO2max (determined
during initial cardiopulmonary evaluation), which corresponds to a heart rate between 70
and 85% of that reached at the peak of exercise. Nevertheless, if the intensity of effort
exceeds 80% of the maximum aerobic capacity, the risk of cardiovascular complications
appears to outweigh the benefits (95). Patients with CHD should be monitored closely
during physiologic testing. The appraiser must have a clear understanding of the effects
of the patient’s clinical status and medications on the physiologic response to exercise.
238 Kontogianni et al.
Low-intensity exercise is generally better accepted by people naive to exercise training,
those who are extremely deconditioned (“out of shape”), and older people. Low-intensity
exercise may result in an improvement in health status with little or no change in physical
fitness. Indeed, light or moderate activity is associated with a reduced risk of death from
any cause among men with established CHD. Furthermore, regular walking or moderate to
heavy gardening has been shown to be sufficient in achieving health benefits. Individuals
with low baseline fitness levels can achieve significant improvements in physical fitness
with a lower training intensity (e.g., 40–50% of heart rate reserve) than that needed by
individuals with a higher baseline fitness level, whereas the latter would need a greater
level of exercise intensity to achieve further improvements in fitness. Deconditioned
individuals may improve their physical fitness with as little as two exercise sessions per
week. Others have shown an improvement in aerobic fitness with exercise intensities as
low as 30% of heart rate reserve in sedentary people. Long-term adherence to this form
of exercise may be poor, however, and the risk of musculoskeletal injury high, especially
in people unaccustomed to exercise (96).
10. NUTRITION COUNSELING AND ADHERENCE ISSUES
IN PATIENTS WITH CVD
Implementation and maintenance of dietary and physical activity changes is of major
importance. Evidence suggests that sustained improvements in diet composition require
individualized and reinforced counseling in patients with CHD (97). Dietitians may be
better able to help patients lower their total and LDL-C levels through nutrition coun-
seling in the short to medium term (98,99). This may be due to the greater amount of
time devoted to advising patients. Others have shown that the effects of a dietitian-based
program for hyperlipidemia were additive to those observed after a physician-delivered
intervention in the US healthcare system (100).
Individualized interventions based on the stages of change and behavioral techniques
are more effective in inducing dietary changes and some improvements in CHD risk
factors, compared with the more traditional methods of provision of information and
exhortation (101–103). Still, corresponding changes in biochemical indexes are not
always present. Stage-matched nutrition counseling promotes progress through stages
of change (104) and future research should focus on feasible ways to keep patients in
the postpreparation stage.
The U.S. Preventive Services Task Force recommends intensive behavioral dietary
counseling for adult patients with hyperlipidemia and other known risk factors for
cardiovascular disease, by primary care clinicians or by referral to other specialists
and/or nutritionists/dietitians (105). Following these recommendations, effective in-
terventions should combine nutrition education with behavior-oriented counseling to
help patients acquire the skills, motivation, and support they need to alter their daily
eating patterns and food preparation practices. Examples of behavior-oriented coun-
seling interventions include teaching self-monitoring, helping patients to set their own
goals and seek social support, providing guidance in shopping and food preparation,
training patients to overcome everyday barriers in making appropriate food choices,
and preventing relapse. In general, these interventions can be described with reference
to the 5-A behavioral counseling framework (adapted from tobacco cessation interven-
tions in clinical care) (106):
Chapter 12 / Nutrition Recommendations and Interventions 239
• Assess: Ask about dietary practices, behavioral health risks, and factors affecting
choice of dietary change goals/methods.
• Advise: Provide clear, specific, and personalized advice on behavior change, includ-
ing information about personal health, harms, and benefits.
• Agree: Collaboratively select appropriate treatment goals and methods based on the
patient’s interest in and willingness to change dietary and physical activity habits. The
clinician employing an empathetic “partnership” approach emphasizes the patient’s
role in interpreting advice and explores, rather than prescribes, how to proceed best.
Patient involvement in decision making about behavior change offers important bene-
fits. Patients who are actively involved in healthcare decisions and engaged in a program
have a greater sense of personal control; their choices are based on realistic expecta-
tions and patient values are promoted. Thus, resistance can be prevented.
• Assist: Using behavior change techniques helps the patient in achieving agreed-
upon goals by acquiring the skills, self-efficacy, and social supports for behavior
change.
• Arrange: Schedule follow-up contacts to provide ongoing assistance and to adjust
the treatment plan as needed, including referral to more intensive or specialized
treatment. As long-term efficacy of lifestyle interventions remains a challenge,
some form of routine follow-up assessment and support through repeat visits, tel-
ephone calls, or other contact is generally deemed necessary to achieve long-term
behavior change.
11. CONCLUSION
Nutrition intervention in CVD represents an evolving scientific area, which expands
from the effects of single nutrients (e.g., fatty acids, fiber) to those of food groups (e.g.,
fruits, vegetables, whole grains) and dietary patterns. The latter, as a holistic approach,
gains continuously more attention and has resulted in scientific data supporting the ben-
eficial role of Mediterranean and DASH diets on CVD prevention and treatment. Fur-
thermore, individuals with CVD should also be given individualized guidance to achieve
a healthy body weight change (at a first stage to reduce their body weight by ~10% from
baseline) and engage in a minimum of 30 min of moderate-intensity aerobic physical
activity for 5 days a week. Nutrition and other health-related professionals should imple-
ment effective interventions combining education with behavior-oriented counseling,
focusing on motivating and supporting patients to change their lifestyle habits.
REFERENCES
1. Hu FB, Willett WC. Optimal diets for prevention of coronary heart disease. JAMA 2002;288:2569–78.
2. Lichtenstein AH, Appel LJ, Brands M, et al.. Diet and lifestyle recommendations revision 2006: a scien-
tific statement from the American Heart Association Nutrition Committee. Circulation 2006;114:82–96.
3. Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol
2002;13:3–9.
4. Fung TT, Chiuve SE, McCullough ML, Rexrode KM, Logroscino G, Hu FB. Adherence to a DASH-style
diet and risk of coronary heart disease and stroke in women. Arch Intern Med 2008;168:713–20.
5. Trichopoulou A, Costacou T, Bamia C, Trichopoulos D. Adherence to a Mediterranean diet and survival
in a Greek population. N Engl J Med 2003;348:2599–608.
240 Kontogianni et al.
6. Graham I, Atar D, Borch-Johnsen K, et al. European guidelines on cardiovascular disease prevention
in clinical practice: executive summary. Fourth Joint Task Force of the European Society of Cardiology
and other societies on cardiovascular disease prevention in clinical practice (constituted by representa-
tives of nine societies and by invited experts). Eur J Cardiovasc Prev Rehabil 2007;14 Suppl 2:E1–40.
7. Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in
Adults–The Evidence Report. National Institutes of Health. Obes Res 1998;6 Suppl 2:51S–209S.
8. Fletcher B, Berra K, Ades P, et al. Managing abnormal blood lipids: a collaborative approach. Circula-
tion 2005;112:3184–209.
9. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP)
Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult
Treatment Panel III). JAMA 2001;285:2486–97.
10. Low-fat diet in myocardial infarction: A controlled trial. Lancet 1965;2:501–4.
11. Burr ML, Fehily AM, Gilbert JF, . Effects of changes in fat, fish, and fibre intakes on death and myo-
cardial reinfarction: diet and reinfarction trial (DART). Lancet 1989;2:757–61.
12. Hu FB, Stampfer MJ, Manson JE, et al. Dietary fat intake and the risk of coronary heart disease in
women. N Engl J Med 1997;337:1491–9.
13. Keys A. Coronary heart disease in seven countries. Circulation 1970;41:I1–198.
14. Van Horn L, McCoin M, Kris-Etherton PM, et al. The evidence for dietary prevention and treatment of
cardiovascular disease. J Am Diet Assoc 2008;108:287–331.
15. Lada AT, Rudel LL. Dietary monounsaturated versus polyunsaturated fatty acids: which is really better
for protection from coronary heart disease? Curr Opin Lipidol 2003;14:41–6.
16. Appel LJ, Sacks FM, Carey VJ, et al. Effects of protein, monounsaturated fat, and carbohydrate intake on
blood pressure and serum lipids: results of the OmniHeart randomized trial. JAMA 2005;294:2455–64.
17. Willett WC, Stampfer MJ, Manson JE, . Intake of trans fatty acids and risk of coronary heart disease
among women. Lancet 1993;341:581–5.
18. Mattson FH, Grundy SM. Comparison of effects of dietary saturated, monounsaturated, and polyun-
saturated fatty acids on plasma lipids and lipoproteins in man. J Lipid Res 1985;26:194–202.
19. Perez-Jimenez F, Lopez-Miranda J, Mata P. Protective effect of dietary monounsaturated fat on arterio-
sclerosis: beyond cholesterol. Atherosclerosis 2002;163:385–98.
20. Kratz M, Cullen P, Kannenberg F, et al. Effects of dietary fatty acids on the composition and oxidiz-
ability of low-density lipoprotein. Eur J Clin Nutr 2002;56:72–81.
21. Riccardi G, Giacco R, Rivellese AA. Dietary fat, insulin sensitivity and the metabolic syndrome. Clin
Nutr 2004;23:447–56.
22. Cassidy A, Albertazzi P, Lise Nielsen I, et al. Critical review of health effects of soyabean phyto-
oestrogens in post-menopausal women. Proc Nutr Soc 2006;65:76–92.
23. Sacks FM, Lichtenstein A, Van Horn L, Harris W, Kris-Etherton P, Winston M. Soy protein, isofla-
vones, and cardiovascular health: an American Heart Association Science Advisory for professionals
from the Nutrition Committee. Circulation 2006;113:1034–44.
24. Truswell AS. Food carbohydrates and plasma lipids–an update. Am J Clin Nutr 1994;59:710S–18S.
25. Srinath Reddy K, Katan MB. Diet, nutrition and the prevention of hypertension and cardiovascular
diseases. Public Health Nutr 2004;7:167–86.
26. Jenkins DJ, Wolever TM, Kalmusky J, et al. Low-glycemic index diet in hyperlipidemia: use of tradi-
tional starchy foods. Am J Clin Nutr 1987;46:66–71.
27. Opperman AM, Venter CS, Oosthuizen W, Thompson RL, Vorster HH. Meta-analysis of the health
effects of using the glycaemic index in meal-planning. Br J Nutr 2004;92:367–81.
28. Rotondo S, de Gaetano G. Protection from cardiovascular disease by wine and its derived products.
Epidemiological evidence and biological mechanisms. World Rev Nutr Diet 2000;87:90–113.
29. Rimm EB, Williams P, Fosher K, Criqui M, Stampfer MJ. Moderate alcohol intake and lower risk of cor-
onary heart disease: meta-analysis of effects on lipids and haemostatic factors. BMJ 1999;319:1523–8.
30. Waterhouse AL. Wine phenolics. Ann N Y Acad Sci 2002;957:21–36.
31. Pace-Asciak CR, Rounova O, Hahn SE, Diamandis EP, Goldberg DM. Wines and grape juices as
modulators of platelet aggregation in healthy human subjects. Clin Chim Acta 1996;246:163–82.
32. Frankel EN, Kanner J, German JB, Parks E, Kinsella JE. Inhibition of oxidation of human low-density
lipoprotein by phenolic substances in red wine. Lancet 1993;341:454–7.
Chapter 12 / Nutrition Recommendations and Interventions 241
33. Flesch M, Schwarz A, Bohm M. Effects of red and white wine on endothelium-dependent vasorelaxa-
tion of rat aorta and human coronary arteries. Am J Physiol 1998;275:H1183–90.
34. Perret B, Ruidavets JB, Vieu C, et al. Alcohol consumption is associated with enrichment of high-den-
sity lipoprotein particles in polyunsaturated lipids and increased cholesterol esterification rate. Alcohol
Clin Exp Res 2002;26:1134–40.
35. Klatsky AL. Alcohol, cardiovascular diseases and diabetes mellitus. Pharmacol Res 2007;55:237–47.
36. Rehm J, Greenfield TK, Rogers JD. Average volume of alcohol consumption, patterns of drinking, and
all-cause mortality: results from the US National Alcohol Survey. Am J Epidemiol 2001;153:64–71.
37. Laatikainen T, Manninen L, Poikolainen K, Vartiainen E. Increased mortality related to heavy alcohol
intake pattern. J Epidemiol Community Health 2003;57:379–84.
38. Tolstrup JS, Jensen MK, Tjonneland A, Overvad K, Gronbaek M. Drinking pattern and mortality in
middle-aged men and women. Addiction 2004;99:323–30.
39. McElduff P, Dobson AJ. How much alcohol and how often? Population based case-control study of
alcohol consumption and risk of a major coronary event. BMJ 1997;314:1159–64.
40. Mukamal KJ, Conigrave KM, Mittleman MA, et al. Roles of drinking pattern and type of alcohol con-
sumed in coronary heart disease in men. N Engl J Med 2003;348:109–18.
41. Mukamal KJ, Jensen MK, Gronbaek M, et al. Drinking frequency, mediating biomarkers, and risk of
myocardial infarction in women and men. Circulation 2005;112:1406–13.
42. Dorn JM, Hovey K, Williams BA, et al. Alcohol drinking pattern and non-fatal myocardial infarction
in women. Addiction 2007;102:730–9.
43. Stranges S, Wu T, Dorn JM, et al. Relationship of alcohol drinking pattern to risk of hypertension: a
population-based study. Hypertension 2004;44:813–9.
44. Athyros VG, Liberopoulos EN, Mikhailidis DP, et al. Association of drinking pattern and alcohol bev-
erage type with the prevalence of metabolic syndrome, diabetes, coronary heart disease, stroke, and
peripheral arterial disease in a Mediterranean cohort. Angiology 2007;58:689–97.
45. Joshipura KJ, Hu FB, Manson JE, et al. The effect of fruit and vegetable intake on risk for coronary
heart disease. Ann Intern Med 2001;134:1106–14.
46. Zyriax BC, Algenstaedt P, Hess UF, et al. Factors contributing to the risk of cardiovascular disease
reflected by plasma adiponectin Data from the coronary risk factors for atherosclerosis in women
(CORA) study. Atherosclerosis 2008;2:403–9.
47. Yannakoulia M, Yiannakouris N, Melistas L, et al. Dietary factors associated with plasma high molecu-
lar and total adiponectin levels in apparently healthy women. Eur J Endocrinol 2008;159:R5–10.
48. Bazzano LA, Serdula MK, Liu S. Dietary intake of fruits and vegetables and risk of cardiovascular
disease. Curr Atheroscler Rep 2003;5:492–9.
49. Slavin J. Why whole grains are protective: biological mechanisms. Proc Nutr Soc 2003;62:129–34.
50. Yannakoulia M, Yiannakouris N, Melistas L, Kontogianni MD, Malagaris I, Mantzoros CS. A die-
tary pattern characterized by high consumption of whole-grain cereals and low-fat dairy products and
low consumption of refined cereals is positively associated with plasma adiponectin levels in healthy
women. Metabolism 2008;57:824–30.
51. Mellen PB, Walsh TF, Herrington DM. Whole grain intake and cardiovascular disease: a meta-analysis.
Nutr Metab Cardiovasc Dis 2008;18:283–90.
52. Hu FB. The role of diet and lifestyle modifications in the statin era. J Am Diet Assoc 2005;105:1718–21.
53. Steffen LM, Kroenke CH, Yu X, et al. Associations of plant food, dairy product, and meat intakes with
15-y incidence of elevated blood pressure in young black and white adults: the Coronary Artery Risk
Development in Young Adults (CARDIA) Study. Am J Clin Nutr 2005;82:1169–77; quiz 1363–4.
54. Jiang R, Jacobs DR, Jr., Mayer-Davis E, et al. Nut and seed consumption and inflammatory markers in
the multi-ethnic study of atherosclerosis. Am J Epidemiol 2006;163:222–31.
55. Olendzki B, Speed C, Domino FJ. Nutritional assessment and counseling for prevention and treatment
of cardiovascular disease. Am Fam Physician 2006;73:257–64.
56. St-Onge MP, Farnworth ER, Jones PJ. Consumption of fermented and nonfermented dairy products:
effects on cholesterol concentrations and metabolism. Am J Clin Nutr 2000;71:674–81.
57. Kontogianni MD, Panagiotakos DB, Chrysohoou C, Pitsavos C, Stefanadis C. Modelling dairy intake
on the development of acute coronary syndromes: the CARDIO2000 study. Eur J Cardiovasc Prev
Rehabil 2006;13:791–7.
242 Kontogianni et al.
58. Svetkey LP, Simons-Morton D, Vollmer WM, . Effects of dietary patterns on blood pressure: sub-
group analysis of the Dietary Approaches to Stop Hypertension (DASH) randomized clinical trial. Arch
Intern Med 1999;159:285–93.
59. Pfeuffer M, Schrezenmeir J. Bioactive substances in milk with properties decreasing risk of cardiovas-
cular diseases. Br J Nutr 2000;84 Suppl 1:S155–9.
60. Tholstrup T. Dairy products and cardiovascular disease. Curr Opin Lipidol 2006;17:1–10.
61. Hu FB, Rimm EB, Stampfer MJ, Ascherio A, Spiegelman D, Willett WC. Prospective study of major
dietary patterns and risk of coronary heart disease in men. Am J Clin Nutr 2000;72:912–21.
62. Fung TT, Willett WC, Stampfer MJ, Manson JE, Hu FB. Dietary patterns and the risk of coronary heart
disease in women. Arch Intern Med 2001;161:1857–62.
63. Fung TT, Rimm EB, Spiegelman D, et al. Association between dietary patterns and plasma biomarkers
of obesity and cardiovascular disease risk. Am J Clin Nutr 2001;73:61–7.
64. Lopez-Garcia E, Schulze MB, Fung TT, et al. Major dietary patterns are related to plasma concentra-
tions of markers of inflammation and endothelial dysfunction. Am J Clin Nutr 2004;80:1029–35.
65. Fung TT, Schulze M, Manson JE, Willett WC, Hu FB. Dietary patterns, meat intake, and the risk of type
2 diabetes in women. Arch Intern Med 2004;164:2235–40.
66. van Dam RM, Rimm EB, Willett WC, Stampfer MJ, Hu FB. Dietary patterns and risk for type 2 diabe-
tes mellitus in U.S. men. Ann Intern Med 2002;136:201–9.
67. Villegas R, Salim A, Flynn A, Perry IJ. Prudent diet and the risk of insulin resistance. Nutr Metab Car-
diovasc Dis 2004;14:334–43.
68. Ding EL, Mozaffarian D. Optimal dietary habits for the prevention of stroke. Semin Neurol 2006;26:11–23.
69. Willett WC, Sacks F, Trichopoulou A, et al. Mediterranean diet pyramid: a cultural model for healthy
eating. Am J Clin Nutr 1995;61:1402S–6S.
70. Serra-Majem L, Roman B, Estruch R. Scientific evidence of interventions using the Mediterranean
diet: a systematic review. Nutr Rev 2006;64:S27–47.
71. Singh RB, Dubnov G, Niaz MA, et al. Effect of an Indo-Mediterranean diet on progression of coronary
artery disease in high risk patients (Indo-Mediterranean Diet Heart Study): a randomised single-blind
trial. Lancet 2002;360:1455–61.
72. de Lorgeril M, Salen P, Martin JL, Monjaud I, Delaye J, Mamelle N. Mediterranean diet, traditional
risk factors, and the rate of cardiovascular complications after myocardial infarction: final report of the
Lyon Diet Heart Study. Circulation 1999;99:779–85.
73. Barzi F, Woodward M, Marfisi RM, Tavazzi L, Valagussa F, Marchioli R. Mediterranean diet and all-
causes mortality after myocardial infarction: results from the GISSI-Prevenzione trial. Eur J Clin Nutr
2003;57:604–11.
74. Sacks FM, Obarzanek E, Windhauser MM, et al. Rationale and design of the Dietary Approaches to
Stop Hypertension trial (DASH). A multicenter controlled-feeding study of dietary patterns to lower
blood pressure. Ann Epidemiol 1995;5:108–18.
75. Moore TJ, Conlin PR, Ard J, Svetkey LP. DASH (Dietary Approaches to Stop Hypertension) diet is
effective treatment for stage 1 isolated systolic hypertension. Hypertension 2001;38:155–8.
76. Obarzanek E, Sacks FM, Vollmer WM, et al. Effects on blood lipids of a blood pressure-lowering diet:
the Dietary Approaches to Stop Hypertension (DASH) Trial. Am J Clin Nutr 2001;74:80–9.
77. Elmer PJ, Obarzanek E, Vollmer WM, et al. Effects of comprehensive lifestyle modification on diet,
weight, physical fitness, and blood pressure control: 18-month results of a randomized trial. Ann Intern
Med 2006;144:485–95.
78. Kris-Etherton PM, Harris WS, Appel LJ. Fish consumption, fish oil, omega-3 fatty acids, and cardio-
vascular disease. Circulation 2002;106:2747–57.
79. Kang JX, Leaf A. Antiarrhythmic effects of polyunsaturated fatty acids. Recent studies. Circulation
1996;94:1774–80.
80. Connor SL, Connor WE. Are fish oils beneficial in the prevention and treatment of coronary artery
disease? Am J Clin Nutr 1997;66:1020S–31S.
81. US Department of Health and Human Services FaDA, Center for Food Safety and Applied Nutrition..
An important message for pregnant women and women of childbearing age who may become pregnant
about the risk of mercury in fish, 2004.
Chapter 12 / Nutrition Recommendations and Interventions 243
82. Kris-Etherton PM, Harris WS, Appel LJ. Omega-3 fatty acids and cardiovascular disease:
new recommendations from the American Heart Association. Arterioscler Thromb Vasc Biol
2003;23:151–2.
83. Devaraj S, Jialal I. The role of dietary supplementation with plant sterols and stanols in the prevention
of cardiovascular disease. Nutr Rev 2006;64:348–54.
84. Plat J, Mensink RP. Plant stanol and sterol esters in the control of blood cholesterol levels: mechanism
and safety aspects. Am J Cardiol 2005;96:15D–22D.
85. Grundy SM. Stanol esters as a component of maximal dietary therapy in the National Cholesterol
Education Program Adult Treatment Panel III report. Am J Cardiol 2005;96:47D–50D.
86. Micallef MA, Garg ML. The lipid-lowering effects of phytosterols and (n-3) polyunsaturated fatty acids
are synergistic and complementary in hyperlipidemic men and women. J Nutr 2008;138:1086–90.
87. Tuomilehto J, Tikkanen MJ, Hogstrom P, et al. Safety assessment of common foods enriched with
natural nonesterified plant sterols. Eur J Clin Nutr 2008.
88. Albanes D, Heinonen OP, Taylor PR, et al. Alpha-tocopherol and beta-carotene supplements and lung
cancer incidence in the alpha-tocopherol, beta-carotene cancer prevention study: effects of base-line
characteristics and study compliance. J Natl Cancer Inst 1996;88:1560–70.
89. Lonn E, Bosch J, Yusuf S, et al. Effects of long-term vitamin E supplementation on cardiovascular
events and cancer: a randomized controlled trial. JAMA 2005;293:1338–47.
90. Miller ER, 3rd, Pastor-Barriuso R, Dalal D, Riemersma RA, Appel LJ, Guallar E. Meta-analy-
sis: high-dosage vitamin E supplementation may increase all-cause mortality. Ann Intern Med
2005;142:37–46.
91. Malinow MR, Bostom AG, Krauss RM. Homocyst(e)ine, diet, and cardiovascular diseases: a state-
ment for healthcare professionals from the Nutrition Committee, American Heart Association. Circu-
lation 1999;99:178–82.
92. Rashid MN, Fuentes F, Touchon RC, Wehner PS. Obesity and the risk for cardiovascular disease. Prev
Cardiol 2003;6:42–7.
93. Thompson PD, Lim V. Physical Activity in the Prevention of Atherosclerotic Coronary Heart Disease.
Curr Treat Options Cardiovasc Med 2003;5:279–85.
94. Haskell WL, Lee IM, Pate RR, et al. Physical activity and public health: updated recommendation for
adults from the American College of Sports Medicine and the American Heart Association. Circula-
tion 2007;116:1081–93.
95. Giada F, Biffi A, Agostoni P, et al. Exercise prescription for the prevention and treatment of cardiovas-
cular diseases: part I. J Cardiovasc Med (Hagerstown) 2008;9:529–44.
96. Ignarro LJ, Balestrieri ML, Napoli C. Nutrition, physical activity, and cardiovascular disease: an
update. Cardiovasc Res 2007;73:326–40.
97. Dalgard C, Thuroe A, Haastrup B, Haghfelt T, Stender S. Saturated fat intake is reduced in patients
with ischemic heart disease 1 year after comprehensive counseling but not after brief counseling. J Am
Diet Assoc 2001;101:1420–9.
98. Thompson RL, Summerbell CD, Hooper L, et al. Relative efficacy of differential methods of dietary
advice: a systematic review. Am J Clin Nutr 2003;77:1052S–7S.
99. Henkin Y, Shai I, Zuk R, et al. Dietary treatment of hypercholesterolemia: do dietitians do it better? A
randomized, controlled trial. Am J Med 2000;109:549–55.
100. Hebert JR, Ebbeling CB, Ockene IS, et al. A dietitian-delivered group nutrition program leads to
reductions in dietary fat, serum cholesterol, and body weight: the Worcester Area Trial for Counseling
in Hyperlipidemia (WATCH). J Am Diet Assoc 1999;99:544–52.
101. Steptoe A, Doherty S, Rink E, Kerry S, Kendrick T, Hilton S. Behavioural counselling in general prac-
tice for the promotion of healthy behaviour among adults at increased risk of coronary heart disease:
randomised trial. BMJ 1999;319:943–7; discussion 947–8.
102. van der Veen J, Bakx C, van den Hoogen H, et al. Stage-matched nutrition guidance for patients at
elevated risk for cardiovascular disease: a randomized intervention study in family practice. J Fam
Pract 2002;51:751–8.
103. Timlin MT, Shores KV, Reicks M. Behavior change outcomes in an outpatient cardiac rehabilitation
program. J Am Diet Assoc 2002;102:664–71.
244 Kontogianni et al.
104. Verheijden MW, Van der Veen JE, Bakx JC, et al. Stage-matched nutrition guidance: stages of
change and fat consumption in Dutch patients at elevated cardiovascular risk. J Nutr Educ Behav
2004;36:228–37.
105. US Preventive Services Task Force. Behavioral counseling in primary care to promote a healthy diet:
recommendations and rationale. Am J Prev Med 2003;24:93–100.
106. Whitlock EP, Orleans CT, Pender N, Allan J. Evaluating primary care behavioral counseling interven-
tions: an evidence-based approach. Am J Prev Med 2002;22:267–84.
13 Medical Nutrition Therapy in the
Treatment of Type 1 and Type 2
Diabetes
Olga Kordonouri, Caroline Apovian,
Lauren Kuhn, Thomas Danne,
and Christos S. Mantzoros
KEY POINTS
• Medical nutrition therapy (MNT), i.e., a goal-oriented approach in developing and in implement-
ing a nutritional plan for the treatment of individuals with diabetes plays a central role in the
care of their patients.
• More specifically, a well-designed nutritional plan is an essential component of the therapeutic
regimen for all diabetics and should be designed in such a way that it should achieve the best
long-term control of diabetes and its complications.
• There is growing evidence that MNT benefits patients with all forms of diabetes and, according
to many, it is the single most important intervention for the prevention and probably treatment
for type 2 diabetics, making it an essential part of diabetes self-management education.
• All members of the team involved in a diabetic patient’s care should be involved in setting
nutrition-related goals, but it is highly recommended that a registered dietitian who is trained
in MNT for diabetics assumes the coordinating role in MNT education and management (1).
• Achieving nutrition-related goals requires the efforts of a multidisciplinary team. Ultimately, the
most important member of that team is the patient as she/he should be the primary decision
maker during the process of implementing a lifestyle change.
• MNT plays an important role in three major areas of diabetes prevention and treatment: pri-
mary prevention, i.e., intervention(s) to prevent obesity and ensuing diabetes; secondary
prevention, after diagnosis, to improve glycemic control and prevent diabetes related compli-
cations; and tertiary prevention to help prevent morbidity and mortality related to managing
the complications of diabetes.
Key Words: Medical nutrition therapy, Diabetes Obesity
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_13,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
245
246 Kordonouri et al.
1. TYPE 1 DIABETES
1.1. Nutrition and Causation of Type 1 Diabetes
Type 1 diabetes is an autoimmune disease with genetic and environmental factors
influencing its development (2). Prospective studies show that islet cell autoimmunity
can begin early in life and that dietary factors can be possible triggers or protective fac-
tors. In particular, a short breastfeeding period and an early introduction of customary for-
mulas based on cow’s milk to infant’s diet have been associated with an increased risk of
diabetes in several ecological and epidemiological studies (3–7). Although both animal
and immunological studies in man further supported the cow’s milk hypothesis (8), the
evidence cannot be regarded as fully conclusive so far. Two metaanalyses led to incon-
sistent results either ascribing the observed weak associations to causal relationships (7)
or to methodological shortcomings of the studies (9). In a recently published nation-
wide case–control study by Rosenbauer et al. (10) in Germany, short breastfeeding and
early introduction of formula feeding (before vs. fifth month or later) were risk factors
of the development of type 1 diabetes in preschool age children [adjusted odd ratios:
1.31 (1.01–1.69) and 1.34 (1.03–1.74), respectively]. In addition, late introduction of
solid food (i.e., after the fourth month of age) was associated with reduced diabetes risk.
Hopefully, in the near future, a worldwide, prospective, randomized, double-blinded
intervention study (Trial to Reduce Diabetes in Genetically at Risk, TRIGR), including
2,160 newborns who carry high-risk HLA alleles and have first degree relative with type
1 diabetes will definitively answer the question of whether avoiding cow’s milk protein
in the first 6–8 months of life will reduce the appearance of multiple diabetes-related
autoantibodies before the age of 6 years or the development of type 1 diabetes up to the
age of 10 years (11). The 6-year autoantibody results will be available in 2012 and the
type 1 diabetes in 2016.
Early introduction of gluten, a wheat protein, in baby’s diet is also thought to contribute
as a trigger of the autoimmune process leading to destruction of pancreatic beta cells. In
animal studies, elimination of this protein from the diet led to significant reduction of
diabetes autoimmunity (12). Since enteral permeability for macromolecules is increased
during the first months of life, it is possible that early introduction of nutrients may lead
to sensitization against several nutritional parameters. Increased enteral permeability
has been already described in patients with type 1 diabetes (13). Furthermore according
to other theories, nutritional parameters like gliadin, a protein fraction of gluten, may
elicit an inflammatory process in gut mucosa leading to an abnormal permeability and
facilitating the exposure of the immune system to potential diabetogenic agents (14). The
effects of the elimination of gluten from the diet of children with a first degree relative
with type 1 diabetes during the first year of life have been studied in an interventional
prospective trial since 2001 (15). Whether this intervention can postpone or even avoid
the development of diabetes-related autoimmunity or even clinical diabetes in this
population will be shown in the near future, since the first results of the BABYDIÄT
Study are expected in 2008.
Vitamin D (1,25 dihydrocholecalciferol) has been discussed as a protective factor for
the development of several diseases like type 1 diabetes, multiple sclerosis, rheumatic
arthritis, hyperthyroidism, and Hashimoto thyroiditis (16) due to its immunomodulating
action. Saggese et al. showed that vitamin D has an immunosuppressive action with in
Chapter 13 / Medical Nutrition Therapy 247
vitro suppression of proliferative T lymphocytes and influences on the production of
cytokine profiles (17). The EURODIAB Trial showed that vitamin D supplementation
during the first year of life was associated with reduced risk of type 1 diabetes (odds ratio
[OR] 0.7, 95% confidence intervals [95%-CI] 0.5–0.9) (18). Hypponen et al. found that
the incidence of type 1 diabetes was significantly lower among subjects who received
a regular daily dose of 2,000 units of vitamin D compared with those without supple-
mentation (OR 0.1, 95%-CI 0.03–0.5) (19). Vitamin D supplementation seems to be a
promising prevention for beta cell autoimmunity, and relative vitamin D deficiency is
now recognized as a pandemic. Some experts suggest that both children and adults should
take 800–1,000 IU of vitamin D per day from dietary and supplementatal sources, if
sunlight cannot provide adequate Vitamin D levels, but this remains to be conclusively
demonstrated. In summary, these recommendations have not yet been recognized
nationally or globally as yet (20).
Fish oil contains not only vitamin D but also polyunsaturated fatty acids (PUFA),
particularly docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA). Long-
chain n-3 fatty acids are incorporated into cell membranes and have antiinflammatory
properties that may be relevant to the prevention of type 1 diabetes, such as decreased
expression of HLA class II molecules on activated human monocytes (21) and re-
duced expression of interleukin 1β. These data suggest that the antiinflammatory n-3
fatty acids such as DHA and EPA may reduce the risk of disease development (22).
The levels of vitamin D and PUFA in newborns depend on the nutritional state of the
mother during gestation (23,24). In a Norwegian study, children from mothers with
fish oil supplementation during pregnancy had a lower risk of type 1 diabetes
(OR 0.3, 95%-CI 0.1–0.8) (25).
In summary, although there is promising evidence that nutrition in early stages of life
may influence the initiation of beta cell autoimmunity in genetically predisposed
individuals, there is currently no conclusive data allowing particular recommendations for
nutritional interventions or vitamin supplementation to prevent the development of type
1 diabetes later in life. Until the results of the large prospective interventional studies are
known, generally accepted guidelines for the nutrition of neonates and infants suggesting
exclusive breastfeeding for the first 4–6 months of life are highly recommended.
1.2. Nutrition and Treatment in Type 1 Diabetes
The first nutrition priority for individuals requiring insulin therapy is to integrate an
insulin regimen into their lifestyle. With the many insulin options now available, an
appropriate insulin regimen can usually be developed to conform to an individual’s pre-
ferred meal routine, food choices, and physical activity pattern.
1.2.1. Nutrition of Children and Adolescents with Type 1 Diabetes
In general, the nutrition of children and adolescents with type 1 diabetes does not
differ from that of their nondiabetic peers. Daily requirements of carbohydrates, fat,
and proteins depend on age, gender, height, weight, levels of daily activity and par-
ticular living conditions such as climate and season. Energy and nutritional require-
ments including vitamins, minerals, and fluids show a higher inter and intraindividual
variability in children and adolescents than in adults. Frequent change of energy and
nutritional requirements accompanied by frequent changing of food types characterize
248 Kordonouri et al.
the nutritional habits of young people. Personal preferences and different eating
habits of the family serve to increase the variability of nutrition among young people
with type 1 diabetes. Once overweight and/or obesity are absent, one can assume that
the physiological regulation of appetite guarantees balanced nutritional and energy
requirements of the growing child. For this reason, nutritional guidelines can only pro-
vide an orientation aid for pediatricians and pediatric diabetologists. Interestingly, the
definition of overweight and obesity in childhood varies between the continents. Thus,
in the US overweight and obesity are defined as body mass index (BMI) exceeding the
85th and 95th percentiles of the US CDC 2000 reference, in the UK the definitions use
the 91st and 98th percentiles of the British 1990 reference, in Germany the 90th and
97th percentiles, respectively (26–28).
The oldest and simplest way to calculate energy needs (in kcal) of children is the one
proposed by Priscilla White according to following formula (29):
age (years) ´ 100 + 1,000 = daily energy requirements (kcal).
The recommended amount of carbohydrates in daily energy intake varies worldwide.
In some countries, it is between 60 and 70%, while in others, such as Europe, it is
between 45 and 60%. The International Society for Pediatric and Adolescent Diabetes
(ISPAD) recommends that carbohydrates should cover at least 50% of daily energy
intake (Table 1) (30). Studies have shown that the higher the percentage of carbohy-
drates, the lower the consumption of fat.
Daily consumption of fiber is recommended to be around 14 g/1,000 kcal. In other
words, for children older than 2 years, daily needs of fiber (in g) are equal with child’s
age (in years) plus five (31).
Fat consumption should not exceed 35% of daily energy intake in children older
than 4 years. To prevent the development of cardiovascular diseases (CVDs) later in life,
it is important to avoid triglycerides with saturated (animal fat) and trans-unsaturated
fatty acids (cookies, chocolate, sweets). Otherwise, the consumption of polyunsaturated
fatty acids (PUFA) of herbal or vegetarian origin or omega-3-fatty acids is recommended
(Table 1) (31).
The calculation of daily protein needs depends on age, gender, and stage of the somatic
development of the child. It varies between 1.2 and 0.8 g per kg body weight per day.
This corresponds to 10–15% of the daily energy intake (Table 1) (31).
Table 1
Distribution of Elementary Nutrients in the Daily Energy Intake in Children and
Adolescents (30)
Carbohydrates >50%
Prefer complex, non-affine, fiber-rich carbohydrates
Moderate saccharose intake
Fat 30–35%
Less than 10% saturated fatty acids
Less than 10% polyunsaturated fatty acids
More than 10% monounsaturated fatty acids
Protein 10–15%
Less protein with increasing age
Chapter 13 / Medical Nutrition Therapy 249
Children and adolescents have higher daily fluid requirements compared with
adults. Daily fluid intake corresponds to 10–15% of child’s body weight, whereas this
is only 2–4% in adults. Usually food items consumed by children are more rich in
fluids than those of adults: solid foods contain ∼60–70% water, fruits and vegetable
almost 90%.
In summary, the following three rules for food consumption could benefit everybody
in choosing healthy food for children and adolescents:
• Abundantly: fluids (possibly energy-free) and plant-based foods
• Moderately: animal products (fat reduced)
• Thriftily: food rich in fat and sugar
For the education of nonobese patients with type 1 diabetes, visual aids like the food
guide pyramid by the US Health Department and Human Services are used (Fig. 1).
Food guide pyramids (such as in Fig. 1 and/or the newer pyramids, see in appendix and
at http://mypyramid.com) suggest optimal nutrition guidelines for each food category,
using a mnemonic graphic of a pyramid with horizontal dividing lines to represent sug-
gested percentages of the daily intake for each food group. For younger children, age-
adjusted food pyramids such as the aid infodienst-pyramid are incorporated into their
training programs (Fig. 2). This uses the traffic light system to indicate recommended
consumption of nutrients (green = abundant, yellow = moderate, red = thriftily), modules
of servings equal to child’s hand size and the 6-5-4-3-2-1-rule (32).
Fig. 1. A recent food guide pyramid by the US Health Department and Human Services. The
food guide pyramids suggest optimal nutrition guidelines for each food category, per day, using
a mnemonic graphic of a pyramid with horizontal dividing lines to represent suggested percent-
ages of the daily diet for each food group. This food guide pyramid was recently replaced with
the new food guide pyramid (see appendix and http://mypyramid.com).
250 Kordonouri et al.
Fig. 2. German example of food pyramid for children using the traffic light system to indicate
recommended consume of nutrients (green = abundant, yellow = moderate, red = thriftily), modules
of servings equal to child’s hand size and the 6-5-4-3-2-1-rule (32). Copyright: aid infodienst.
1.3. Nutrition and Treatment of Type 1 Diabetes
For individuals receiving “conventional therapy,” which is defined as prebreakfast
and presupper injections of short and intermediate acting insulin, food should be kept
consistent in terms of timing and amount. For those using “intensive therapy,” which
consists of three or more injections of insulin or use of an insulin pump, individuals
should be taught to adjust their meal and snack at the times of insulin doses based on
their total carbohydrate content.
Current knowledge about the content of carbohydrates in the daily nutrition of patients
with type 1 diabetes suggests using different goals depending on the type of treatment.
Patients treated with conventional therapy must calculate the amount of carbohydrate
to avoid decreases of blood glucose levels after insulin injection. Patients treated with
intensified insulin regimes should be aware of the amount of carbohydrate in their food
in order to calculate the amount of insulin they need to avoid nonphysiological increases
of postprandial blood glucose. Patients treated with a continuous subcutaneous insulin
infusion (CSII) pump system have the possibility of using three different kinds of boluses
to regulate their postprandial glycemic profiles: normal bolus delivering insulin rapidly
as a shot, square-wave bolus delivering insulin for an extended period of time (h), and
dual-wave bolus in which a certain amount of insulin is released immediately and the
rest over an extended period of time (33). Use of dual-wave bolus may be more effective
than the use of a normal bolus to control postprandial glucose profile after meals rich
in carbohydrates and fat (33).
To achieve optimal glycemic profiles during conventional insulin treatment, food
intake has to be distributed in frequent and small meals. A dietary plan consists mostly
Chapter 13 / Medical Nutrition Therapy 251
of three main meals (breakfast, lunch, and dinner), two snacks in between and one more
before bedtime. During intensified insulin treatment with differentiated basal and prandial
insulin substitution, however, patients are very flexible in their daily routine. They can
decide when and how much they want to eat. The most important prerequisite is their
ability to know and estimate the nutrient content of meals to calculate the amount of
insulin they need for the planned meal.
Several methods can be used to estimate the nutrient content of meals, including
carbohydrate counting, the exchange system, and experience-based estimation. The
DAFNE (Dose Adjustment for Normal Eating) study demonstrated that patients can
learn how to use glucose testing to better match insulin to carbohydrate intake (34,35).
Improvement in HbA1c without a significant increase in severe hypoglycemia was
demonstrated, as were positive effects on quality of life, satisfaction with treatment,
and psychological well-being, even though increases in the number of insulin injections
and blood glucose tests were necessary.
For planned exercise, reduction in insulin dosage is the preferred method to prevent
hypoglycemia. For unplanned exercise, intake of additional carbohydrate is usually
needed. Moderate-intensity exercise increases glucose utilization by 2–3 mg/kg/min
above usual requirements (1). For that reason, high to normal levels of blood glucose
between 150 and 180 mg/dL are the aim before physical activities. Patients on insulin
treatment are educated to eat 10–15 g of carbohydrates before sports if blood glucose
levels are below 150 mg/dL.
MNT has been reported to decrease HbA1c by ∼1% in type 1 diabetic patients (36).
2. TYPE 2 DIABETES
2.1. Nutrition and Prevention of Type 2 Diabetes
For individuals at risk for diabetes or who have prediabetes, the goals of MNT are
to decrease diabetes and CVD risk by encouraging moderate weight loss maintained by
healthy food choices and physical activity (36). Evidence from epidemiologic studies
suggests that certain individual foods and dietary patterns may help prevent type 2 diabetes.
There is also accumulating evidence from clinical trials in favor of lifestyle changes that
incorporate moderate weight loss and increasing leisure time physical activity. Use of
certain medications could also achieve similar goals but use of medications for this
purpose is not considered cost-effective and is not currently recommended.
Epidemiologic evidence suggests that certain dietary components and overall diet-
quality may reduce the risk of developing type 2 diabetes. An evaluation of available
observational studies found strong evidence that a diet high in soluble or insoluble fiber
can reduce the risk of type 2 diabetes. Somewhat weaker evidence suggests an association
between diets low in glycemic index and reduced risk of disease (37). Prospective cohort
studies also suggest that diets higher in whole grains, cereal fiber, and magnesium may
lower the risk of type 2 diabetes (38). Certain individual foods such as coffee (39,40)
and nuts (41) have also been associated with reduced diabetes risk in cohort studies,
while increased consumption of meat (42–44) and sugar-sweetened beverages (45) may
increase the risk. Interestingly, our own studies have recently demonstrated that these
beneficial diets also increase circulating levels of adiponectin, an adipocyte-secreted
252 Kordonouri et al.
hormone and levels of which are a strong inverse predictor of insulin resistance and
diabetes (46–48). Prospective investigations also suggest that certain healthy dietary pat-
terns may help prevent diabetes. In an analysis of 80,029 women from the Nurses’ Health
Study, those with the highest adherence to a healthy diet, as measured by the Alternative
Healthy Eating Index, had lower risk of type 2 diabetes during 18 years of follow-up
(RR = 0.64, 95% CI 0.58–0.71) (49). Benefits of many individual dietary components
in reducing the risk of diabetes have yet to be confirmed by interventional studies.
Prospective studies suggest that even modest sustained weight loss is associated with
dramatically reduced risk of type 2 diabetes (50,51). Leisure time physical activity has
also been associated with lower risk of developing diabetes mellitus in cohort studies
(52–54), including moderate activities such as walking (55). Recent interventional
studies have sought to determine whether a combined program of moderate weight
loss and physical activity can prevent type 2 diabetes among those at high risk. The
Diabetes Prevention Program (56) randomized trial compared the effects of placebo,
metformin, and intensive lifestyle intervention on prevention of type 2 diabetes in
3,234 subjects with impaired glucose tolerance. The goal of the lifestyle-modification
intervention was to achieve 7% weight loss through a low-calorie, low-fat diet and to
engage in at least 150 min of physical activity per week. After an average follow-up of
2.8 years, the incidence rate of diabetes was 11.0, 7.8, and 4.8 cases per 100 person-
years in the placebo, metformin, and lifestyle groups, respectively. Incidence of type
2 diabetes was reduced by 58% in the lifestyle group and by 31% in the metformin
group compared with placebo (56). The Finnish Diabetes Prevention Study also found
that a similar intensive lifestyle intervention involving dietary counseling and increased
physical activity resulted in improved glucose levels, lipid markers, and BMI after 3
years compared with controls (57). Extended follow-up of this study found that those
who participated in the lifestyle intervention continued to have reduced risk of type 2
diabetes for years after the intervention ended (58).
2.2. Nutrition and Treatment of Type 2 Diabetes
2.2.1. Goals
There are several goals of MNT for individuals with diabetes, as recommended by the
American Diabetes Association (ADA). The first goal is for the patient to achieve and
maintain blood glucose levels in the normal range or as close to normal as is safely pos-
sible (36). The ADA guidelines for normal blood glucose levels are as follows: Hemo-
globin A1c (HbA1c) <6.5%, preprandial plasma glucose <110 mg/dL, and postprandial
glucose <140 mg/dL. Another aim of MNT is to aid patients with diabetes in achieving
and maintaining a lipid and lipoprotein profile that reduces their risk for vascular disease
(36). This includes the maintenance of optimal LDL-C levels, HDL-C levels, triglycerides,
and total cholesterol. Effective MNT should also allow patients to achieve blood pressure
levels in the normal range or as close to normal as is safely possible and to achieve a
healthy BMI.
After diagnosis, medical nutrition therapists can use the initial consultation framework
provided by the American Dietetic Associations Care Manual (59) in developing their
initial care plan. Although every patient interaction will be different and the care plan
will undoubtedly be tailored to reflect this, the framework can be helpful in providing
consistency of care to all patients. When working with a patient who has been recently
Chapter 13 / Medical Nutrition Therapy 253
diagnosed with diabetes, the framework recommends educating the patient on basic nutri-
tion, diabetes nutrition guidelines, and beginning strategies for altering eating patterns.
Continuing self-management counseling includes both management skills and lifestyle
changes. Flexibility in food planning should always be addressed. Topics emphasized or
chosen are based on the following factors related to the individual (59): choice, lifestyle,
levels of nutrition knowledge, and experience in planning, purchasing, and preparing
foods and meals. After the initial visit, it is important to establish a timeline for follow-
up, which helps to identify expected outcomes (e.g., preprandial and postprandial blood
glucose goals) and determine response to and effectiveness of nutritional care.
Patients with diabetes cannot rely on counting calories alone since carbohydrates
are the major determinant of postprandial glucose levels. The amount of carbohydrate
ingested is usually the primary determinant of postprandial response, but the type of
carbohydrate can also have an effect. Patients may have the impression that there is a
diabetic diet and that once type 2 diabetes is diagnosed all sugar(s) must be avoided.
In reality, people with diabetes can eat the same foods as those who do not have the
disease, but they must be sure to match insulin and insulin secretagogues to the carbo-
hydrate content of their meals. Patients can be educated to do this in a variety of ways
including the use of exchange lists and carbohydrate counting, the most widely used
method. In educating a patient on carbohydrate counting, the first step is to teach the
patient which foods contain carbohydrates (starches, fruits, starchy vegetables, milk, and
sweets). For diabetes meal planning, one serving of a food with carbohydrates has about
15 g of carbohydrates. The number of grams of carbohydrates that a person can eat each
day or at each meal is determined by factors such as the patient’s weight, whether or not
a calorie-restricted diet to induce weight loss is necessary, timing, and type of physical
activity, and medications. For many adults, eating 3–5 servings of carbohydrate foods
at each meal and one or two carbohydrate servings for each snack is effective. A meal
plan that incorporates carbohydrate counting would highlight the number of servings to
select per meal to avoid exceeding the amount of grams of carbohydrates per meal. This
structure and consistency is a major tool in maintaining glucose control. Research has
not demonstrated that one method of assessing the relationship between carbohydrate
intake and blood glucose response is better than another. However, it is very important
that individuals adhere to a system that they understand and which they can follow
consistently – whether it is carbohydrate counting, the exchange system, or monitoring
carbohydrate using experienced-based estimation.
In the US, the recommended daily allowance for carbohydrates is 130 g/day. Since
there is no data regarding very low intake of carbohydrates specifically in patients with
diabetes, diets restricting total carbohydrates to <130 g/day are not recommended in the
management of diabetes. High-carbohydrate diets (55% of total energy from carbohy-
drates) increase postprandial plasma glucose, insulin, and triglycerides when compared
with high-monounsaturated fat diets (60), but diets restricting carbohydrates to <130 g/
day have not been proven to be sustainable.
Individuals with diabetes should be encouraged to consume vegetables, fruits, legumes,
and whole and minimally processed grains as their major source of carbohydrates.
Refined carbohydrates or processed grains and starchy foods (especially pasta, white
bread, low-fiber cereal, and white potatoes) are not recommended and should be
consumed in limited quantities.
254 Kordonouri et al.
Current guidelines recommend at least 14 g/1,000 kcal of fiber per day for a healthy
individual. For type 2 diabetics, available evidence suggests that consuming a high-fiber
diet of at least 50 g of fiber per day leads to reduction in glycemia, hyperinsulinemia,
and lipemia by slowing down the digestion of carbohydrates (61). However, a goal of
50 g/day may not be realistic for the majority of the population due to barriers including
taste and gastrointestinal side effects. These side effects can be diminished by increas-
ing fiber in the diet gradually (∼3–5 g/day) until the recommended goal is met and by
increasing fluid intake. Increased fiber intake can be achieved by choosing a variety of
fiber-containing foods such as legumes, fiber-rich cereals (>5 g fiber/serving), fruits,
vegetables, and whole grain products, all of which provide vitamins, minerals, and other
substances important for good health.
With respect to dietary fat, the primary goal for individuals with diabetes is to limit
saturated fatty acids, trans-fatty acids, and cholesterol intake to reduce the risk for CVD.
Saturated and trans-fatty acids are the principal dietary determinants of plasma LDL
cholesterol. In nondiabetic individuals, reducing saturated and trans-fatty acids and
cholesterol intakes decreases plasma total and LDL cholesterol (62). Saturated and
trans-fat should make up <10% (59) of caloric intake, but the most current recom-
mendations state that <7% of the diet should consist of saturated fat alone (36). Foods
high in saturated fat, including beef, pork, lamb, and high fat dairy products (e.g., cream
cheese, whole milk, or full fat cheese) are not recommended and should be consumed only
in small amounts. Foods high in trans-fats (e.g., fast foods, commercially baked goods,
some margarines) should also be avoided.
Fat restriction to <30% of the diet can decrease total and LDL cholesterol as well
as obesity (63,64). However, it is important to notice when patients consuming a low
fat diet begin to supplement their diet with a greater proportion of carbohydrates. High
carbohydrate intake leads to increased postprandial blood glucose and increased fasting
triglycerides (65). Because of these nuances, it is very important to individualize fat
and carbohydrate intake for optimal results in a particular patient. If a low-fat diet is
not producing desired outcomes, it may be necessary to shift ratios and evaluate caloric
intake (66).
Certain types of fat may have beneficial effects for individuals with diabetes. In those
individuals who are already hyperlipidemic, studies have shown that mono and polyunsatu-
rated fats have beneficial effects on lipid profiles (67). Very-long-chain n-3 polyunsaturated
fatty acid supplements have been shown to lower plasma triglyceride levels in individuals
with type 2 diabetes who are hypertriglyceridemic. Although the accompanying small rise
in plasma LDL cholesterol is of concern, an increase in HDL cholesterol may offset this
concern (68). Recommended fats such as olive oil and walnuts, which have high mono
and polyunsaturated fats, should displace high saturated fat and trans fat-containing foods
from the diet. Other recommended mono and polyunsaturated fats include canola oil, nuts/
seeds, and fish, particularly those high in omega-3 fatty acids. For instance, oily fish (e.g.,
salmon, herring, trout, sardines, fresh tuna) two times a week is an ample source of omega
3 fatty acids. More details about supplemental dose, if taken as a pill, can be found in the
relevant chapter of this book.
Plant sterol and stanol esters block the intestinal absorption of dietary and biliary cho-
lesterol. In the general public and in individuals with type 2 diabetes (21), intake of 2 g/day
plant sterols and stanols has been shown to lower plasma total and LDL cholesterol (36).
Chapter 13 / Medical Nutrition Therapy 255
Currently, there is a wide range of new food products that contain plant sterols. Because
these are fats which carry 9 cal/g, it should be advised that, like mono and polyunsaturated
fats, these should be avoided to prevent weight gain. Supplements are also available.
Individuals with diabetes have the same needs for protein as those who do not have
diabetes. The Dietary Reference Intakes’ acceptable macronutrient distribution range for
protein is 10–35% of energy intake, with 15% being the average adult intake in the US
and Canada (69). There are some special considerations related to protein for anyone that
shows signs of kidney disease. Protein intake for those with renal problems will need to be
modified. A diet that includes a lower amount of protein is recommended for these patients,
but it is important to emphasize that protein does not need to be lowered to a point that
may jeopardize the overall nutrition quality of their diet, and thus a nephrologist should be
consulted before making any dietary changes. Although there is no evidence that strongly
supports reduction of protein intake in diabetics without renal complications, studies
have shown that in subjects with diabetes and microalbuminuria, reduction of protein
intake to 0.8–1.0 g/kg/day decreased urinary albumin excretion rate and decreased rate
of decline in glomerular filtration. This requires patients to limit meat, fish, and poultry
intake to 3–5 oz/day, which may be difficult for some patients to achieve at first. Because
individuals with diabetes are at an increased risk for cardiac disease, it is suggested that
they first try to decrease protein in their diet from animal sources high in saturated fats.
Favorable protein sources include fish, skinless poultry, nonfat or low-fat dairy, legumes,
tofu, and tempeh. There is no evidence at this time to suggest that vegetable proteins have
any nephrotoxic effects and these do not need to be limited.
High-protein diets are not recommended as a method for weight loss at this time.
Although high protein diets may be effective at producing short-term weight loss results
and improved blood glucose control, the long-term effects of protein intake >20% of
calories on diabetes management and its complications, including effects on the kidneys,
remain unknown.
Alternative sweeteners may be used to reduce sugar intake for diabetics. Sorbitol,
mannitol, and fructose are commonly used sweeteners that have a lower glycemic effect
than glucose or sucrose. However, they do contain the same amount of calories as glucose
and sucrose (4 cal/g), a fact that is usually forgotten. Sorbitol and mannitol may cause
bloating and diarrhea when >30 g/day are consumed (66). Though fructose produces a
lower postprandial glucose response when it replaces sucrose or starch in the diet, there
are concerns that it may adversely affect the lipid profile. Reduced calorie sweeteners
approved by the FDA include sugar alcohols such as erythritol, isomalt, lactitol, maltitol,
mannitol, sorbitol, xylitol, tagatose, and hydrogenated starch hydrolysates. Sugar alco-
hols contain about 2 cal/g. When calculating carbohydrate content of foods containing
sugar alcohols, subtraction of half the sugar alcohol grams from total carbohydrate
grams is appropriate. There is no evidence at this time to suggest that the amounts of
sugar alcohols likely to be consumed will reduce glycemia, energy intake, or weight.
The use of sugar alcohols appears to be safe; however, like sorbitol and mannitol, they
may cause gastrointestinal upset. The FDA has approved five nonnutritive sweeteners
for use in the US. These are acesulfame potassium, aspartame, neotame, saccharin, and
sucralose, compounds that are 200 times sweeter than sugar, allowing their use in very
small quantities. This makes them beneficial to diabetics because they add virtually no
caloric or nutritional value to food (65). However, they may be used in foods that contain
256 Kordonouri et al.
other sources of carbohydrates and calories such as ice cream, cookies, and puddings.
Thus, not only the energy these compounds provide but total energy must be taken into
account (1).
Complete abstinence from alcohol is not necessary for diabetics. If alcohol is con-
sumed, intake should be consistent with the 2005 USDA Dietary Guidelines for Ameri-
cans, which recommend no more than one drink per day for women and two drinks per
day for men. For education purposes, one alcohol containing beverage is defined as 12 oz
beer, 5 oz wine, or 1.5 oz distilled spirits. Each contains >15 g alcohol. Alcohol itself has
minimal effects on plasma glucose and serum insulin levels. However, when coingested
with carbohydrates, blood glucose may rise. Diabetic patients should note that, when
using insulin or insulin secretagogues, alcohol should be consumed with food to avoid
hypoglycemia (1,66). Alcohol should be avoided in patients with hypertriglyceridemia,
however, because it causes increased elevation in postprandial triglyceride levels (65).
Individuals with diabetes should be aware of the importance of acquiring daily vitamin
and mineral requirements from natural food sources and a balanced diet. In select groups
such as the elderly, pregnant, or lactating women, strict vegetarians, or those on calorie-
restricted diets, a multivitamin supplement may be needed (66). Uncontrolled diabetes
is often associated with micronutrient deficiencies. With regard to antioxidants, there
is no clear evidence that they improve glycemic control and long-term complications of
diabetes. In contrast, there is some evidence of possible harm in taking high doses of
antioxidant supplements such as vitamin E and carotene. Finally, there is no evidence at
this time that antioxidant supplementation has any role in the prevention of CVD (1).
Chromium, potassium, magnesium, and possibly zinc deficiency may aggravate
carbohydrate intolerance. Serum levels of potassium and magnesium can be checked
and should be replaced as needed, but there is no clear evidence that zinc or chromium
replacement benefit those with diabetes, although definitive trials have yet to be per-
formed. Thus, it is uncertain whether herbal or vitamin supplementation is beneficial to
individuals with diabetes unless there is an established micronutrient deficiency. Because
commercially available products are not standardized, vary in the content of active in-
gredients, and have the potential to interact with other medications, it is important that
health care providers are aware of the use of these products by their diabetic patients.
The following popular herbals have been shown to lower blood glucose (an effect which
may potentially interact with blood glucose lowering medications): Ginseng (Panax
ginseng); Fenugreek (Trigonella foenum-graecum); Bitter Melon (Momordica charan-
tia); Garlic (Allium sativum). Their intake should also be taken under consideration by
practicing physicians.
3. EXERCISE
3.1. Overview
Exercise increases both insulin sensitivity and uptake in skeletal muscle during and
after activity. Exercise, unless otherwise contraindicated, should thus be included in all
diabetic treatment regimens, whether the individual is overweight or of normal body
weight, unless it is otherwise contraindicated. Exercise is the best predictor of sustained
weight loss and, notably, it decreases central body fat (which is highly associated with
insulin resistance and CVD). The greatest benefit that diabetics gain from regular
Chapter 13 / Medical Nutrition Therapy 257
exercise is reduction of cardiovascular risk factors including reduction in blood pressure,
lowering very low density and low density lipoproteins as well as triglycerides, and
improvement of the lipid profile. Exercise also raises high density lipoproteins.
Prolonged exercise can potentiate the effect of oral agents as well as the effect of
insulin on blood glucose levels. It may also reduce hepatic glucose output and decrease
both fasting and postprandial glycemia. Because its insulin sensitizing effects taper
after 48 h, people should engage in at least 150 min/week of moderate-intensity aerobic
physical activity 3–4 times weekly, without intervals of more than 48 h in between
sessions. Resistance training is also effective in improving glycemia, and, in the absence
of proliferative retinopathy, people with type 2 diabetes can be encouraged to perform
resistance exercise three times a week.
However, if weight loss is the goal, it may be necessary to exercise 5–6 times per
week. Individuals should gradually increase duration and intensity of exercise as is
tolerable. Because of the hypoglycemic effects of exercise, patients should monitor
their glucose and try to avoid hypoglycemia. With the introduction of regular exercise
into the treatment regimen, patients will likely require less insulin and may reduce their
need for oral agents.
Most patients can safely engage in light walking; however, it may be necessary to
perform cardiac stress testing before patients can engage in regular strenuous exercise.
A stress test is highly recommended for inactive people who are planning to start an
exercise regimen above the age of 35 years. Strenuous exercise is contraindicated in
individuals with significant diabetic complications including active proliferative retin-
opathy, neuropathy, and established significant CVD (70,71).
Patients should be encouraged to choose their own modes of physical activity.
Sustained interest in the exercise program is the key for long-term maintenance, and
thus will have the greatest impact on achievement of weight, lipid profile and glycemic
goals as well as prevention of complications of diabetes (72). Precautions should be taken
for patients taking agents such as adrenergic blocking agents, alcohol, or salicylates,
which might make patients more susceptible to exercise-induced hypoglycemia.
4. CONCLUSION
In conclusion, MNT benefits patients with all forms of diabetes, and in the case of
type 2 diabetes, it is the single most important intervention for prevention and treat-
ment. Achieving the goals of MNT requires the efforts of a multidisciplinary team with
expertise in behavioral techniques focusing on dietary change as well as exercise therapy.
MNT goals should include attention to weight, lipid profile, and glycemic status to have
its greatest impact on cardiovascular improvement.
REFERENCES
1. Bantle JP, Wylie-Rosett J, Albright AL et al. Nutrition recommendations and interventions for diabetes–2006:
a position statement of the American Diabetes Association. Diabetes Care 2006; 29(9):2140–2157.
2. Soltesz G. Diabetes in the young: a paediatric and epidemiological perspective. Diabetologia 2003;
46(4):447–454.
3. Blom L, Dahlquist G, Nystrom L, Sandstrom A, Wall S. The Swedish childhood diabetes study–social
and perinatal determinants for diabetes in childhood. Diabetologia 1989; 32(1):7–13.
258 Kordonouri et al.
4. Dahlquist G, Blom L, Lonnberg G. The Swedish Childhood Diabetes Study–a multivariate analysis of
risk determinants for diabetes in different age groups. Diabetologia 1991; 34(10):757–762.
5. Virtanen SM, Rasanen L, Ylonen K et al. Early introduction of dairy products associated with increased
risk of IDDM in Finnish children. The Childhood in Diabetes in Finland Study Group. Diabetes 1993;
42(12):1786–1790.
6. Kostraba JN, Cruickshanks KJ, Lawler-Heavner J et al. Early exposure to cow’s milk and solid foods in
infancy, genetic predisposition, and risk of IDDM. Diabetes 1993; 42(2):288–295.
7. Gerstein HC. Cow’s milk exposure and type I diabetes mellitus. A critical overview of the clinical
literature. Diabetes Care 1994; 17(1):13–19.
8. Harrison LC, Honeyman MC. Cow’s milk and type 1 diabetes: the real debate is about mucosal immune
function. Diabetes 1999; 48(8):1501–1507.
9. Norris JM, Scott FW. A meta-analysis of infant diet and insulin-dependent diabetes mellitus: do biases
play a role?. Epidemiology 1996; 7(1):87–92.
10. Rosenbauer J, Herzig P, Kaiser P, Giani G. Early nutrition and risk of Type 1 diabetes mellitus–a nation-
wide case-control study in preschool children. Exp Clin Endocrinol Diabetes 2007; 115(8):502–508.
11. TRIGR Study Group. Study design of the Trial to Reduce IDDM in the Genetically at Risk (TRIGR).
Pediatr Diabetes 2007; 8(3):117–137.
12. Norris JM, Barriga K, Klingensmith G et al. Timing of initial cereal exposure in infancy and risk of islet
autoimmunity. JAMA 2003; 290(13):1713–1720.
13. Couper JJ, Steele C, Beresford S et al. Lack of association between duration of breast-feeding or intro-
duction of cow’s milk and development of islet autoimmunity. Diabetes 1999; 48(11):2145–2149.
14. Akerblom HK, Virtanen SM, Ilonen J et al. Dietary manipulation of beta cell autoimmunity in infants
at increased risk of type 1 diabetes: a pilot study. Diabetologia 2005; 48(5):829–837.
15. Ziegler AG, Schmid S, Huber D, Hummel M, Bonifacio E. Early infant feeding and risk of developing
type 1 diabetes-associated autoantibodies. JAMA 2003; 290(13):1721–1728.
16. Arnson Y, Amital H, Shoenfeld Y. Vitamin D and autoimmunity: new aetiological and therapeutic
considerations. Ann Rheum Dis 2007; 66(9):1137–1142.
17. Saggese G, Federico G, Balestri M, Toniolo A. Calcitriol inhibits the PHA-induced production of IL-2
and IFN-gamma and the proliferation of human peripheral blood leukocytes while enhancing the sur-
face expression of HLA class II molecules. J Endocrinol Invest 1989; 12(5):329–335.
18. Vitamin D supplement in early childhood and risk for Type I (insulin-dependent) diabetes mellitus. The
EURODIAB Substudy 2 Study Group. Diabetologia 1999; 42(1):51–54.
19. Hypponen E, Laara E, Reunanen A, Jarvelin MR, Virtanen SM. Intake of vitamin D and risk of type 1
diabetes: a birth-cohort study. Lancet 2001; 358(9292):1500–1503.
20. Holick MF, Chen TC. Vitamin D deficiency: a worldwide problem with health consequences. Am J
Clin Nutr 2008; 87(4):1080S–1086S.
21. Lee YM, Haastert B, Scherbaum W, Hauner H. A phytosterol-enriched spread improves the lipid pro-
file of subjects with type 2 diabetes mellitus–a randomized controlled trial under free-living conditions.
Eur J Nutr 2003; 42(2):111–117.
22. Stene LC, Joner G. Use of cod liver oil during the first year of life is associated with lower risk of
childhood-onset type 1 diabetes: a large, population-based, case-control study. Am J Clin Nutr 2003;
78(6):1128–1134.
23. Nettleton JA. Are n-3 fatty acids essential nutrients for fetal and infant development? J Am Diet Assoc
1993; 93(1):58–64.
24. Delvin EE, Salle BL, Glorieux FH, Adeleine P, David LS. Vitamin D supplementation during preg-
nancy: effect on neonatal calcium homeostasis. J Pediatr 1986; 109(2):328–334.
25. Stene LC, Ulriksen J, Magnus P, Joner G. Use of cod liver oil during pregnancy associated with lower
risk of Type I diabetes in the offspring. Diabetologia 2000; 43(9):1093–1098.
26. Krebs NF, Jacobson MS. Prevention of pediatric overweight and obesity. Pediatrics 2003; 112(2):424–430.
27. Hall DM, Cole TJWhat use is the BMI?. Arch Dis Child 2006; 91(4):283–286.
28. Reinehr T, de SG, Toschke AM, Andler W. Comparison of metabolic syndrome prevalence using eight
different definitions: a critical approach. Arch Dis Child 2007; 92(12):1067–1072.
29. White P, Graham CA. The child with diabetes. In: Marble A, White P, Bradley RF, Krall LP, editors.
Joslin’s Diabetes mellitus. Philadelphia: Lea & Febinger; 1971, p. 339ff.
Chapter 13 / Medical Nutrition Therapy 259
30. ISPAD Guidelines 2000. Zeist Netherlands: Medforum; 2000.
31. Gidding SS, Dennison BA, Birch LL et al. Dietary recommendations for children and adolescents: a
guide for practitioners: consensus statement from the American Heart Association. Circulation 2005;
112(13):2061–2075.
32. aid infodienst e.V. Die aid-Ernahrungspyramide: Richtig essen lehren und lernen. Bonn: 2003.
33. Chase HP, Saib SZ, MacKenzie T, Hansen MM, Garg SK. Post-prandial glucose excursions follow-
ing four methods of bolus insulin administration in subjects with type 1 diabetes. Diabet Med 2002;
19(4):317–321.
34. DAFNE Study Group. Training in flexible, intensive insulin management to enable dietary freedom in
people with type 1 diabetes: dose adjustment for normal eating (DAFNE) randomised controlled trial.
BMJ 2002; 325(7367):746.
35. Knowles J, Waller H, Eiser C et al. The development of an innovative education curriculum for 11–16
yr old children with type 1 diabetes mellitus (T1DM). Pediatr Diabetes 2006; 7(6):322–328.
36. Bantle JP, Wylie-Rosett J, Albright AL et al. Nutrition recommendations and interventions for diabetes:
a position statement of the American Diabetes Association. Diabetes Care 2008; 31 Suppl 1:S61–S78.
37. Riccardi G, Rivellese AA, Giacco R. Role of glycemic index and glycemic load in the healthy state, in
prediabetes, and in diabetes. Am J Clin Nutr 2008; 87(1):269S–274S.
38. Schulze MB, Hu FB Primary prevention of diabetes: what can be done and how much can be pre-
vented?. Annu Rev Public Health 2005; 26:445–467.
39. Rosengren A, Dotevall A, Wilhelmsen L, Thelle D, Johansson S. Coffee and incidence of diabetes in
Swedish women: a prospective 18-year follow-up study. J Intern Med 2004; 255(1):89–95.
40. Salazar-Martinez E, Willett WC, Ascherio A et al. Coffee consumption and risk for type 2 diabetes
mellitus. Ann Intern Med 2004; 140(1):1–8.
41. Jiang R, Manson JE, Stampfer MJ, Liu S, Willett WC, Hu FB. Nut and peanut butter consumption and
risk of type 2 diabetes in women. JAMA 2002; 288(20):2554–2560.
42. Fung TT, Schulze M, Manson JE, Willett WC, Hu FB. Dietary patterns, meat intake, and the risk of type
2 diabetes in women. Arch Intern Med 2004; 164(20):2235–2240.
43. Schulze MB, Manson JE, Willett WC, Hu FB. Processed meat intake and incidence of Type 2 diabetes
in younger and middle-aged women. Diabetologia 2003; 46(11):1465–1473.
44. Song Y, Manson JE, Buring JE, Liu S. A prospective study of red meat consumption and type 2 diabetes
in middle-aged and elderly women: the women’s health study. Diabetes Care 2004; 27(9):2108–2115.
45. Schulze MB, Manson JE, Ludwig DS et al. Sugar-sweetened beverages, weight gain, and incidence of
type 2 diabetes in young and middle-aged women. JAMA 2004; 292(8):927–934.
46. Mantzoros CS, Williams CJ, Manson JE, Meigs JB, Hu FB. Adherence to the Mediterranean dietary
pattern is positively associated with plasma adiponectin concentrations in diabetic women. Am J Clin
Nutr 2006; 84(2):328–335.
47. Qi L, Meigs JB, Liu S, Manson JE, Mantzoros C, Hu FB. Dietary fibers and glycemic load, obesity, and
plasma adiponectin levels in women with type 2 diabetes. Diabetes Care 2006; 29(7):1501–1505.
48. Yannakoulia M, Yiannakouris N, Melistas L, Kontogianni MD, Malagaris I, Mantzoros CS. A die-
tary pattern characterized by high consumption of whole-grain cereals and low-fat dairy products and
low consumption of refined cereals is positively associated with plasma adiponectin levels in healthy
women. Metabolism 2008; 57(6):824–830.
49. Fung TT, McCullough M, van Dam RM, Hu FB. A prospective study of overall diet quality and risk of
type 2 diabetes in women. Diabetes Care 2007; 30(7):1753–1757.
50. Resnick HE, Valsania P, Halter JB, Lin X. Relation of weight gain and weight loss on subsequent dia-
betes risk in overweight adults. J Epidemiol Community Health 2000; 54(8):596–602.
51. Moore LL, Visioni AJ, Wilson PW, D’Agostino RB, Finkle WD, Ellison RC, Can sustained weight loss
in overweight individuals reduce the risk of diabetes mellitus?. Epidemiology 2000; 11(3):269–273.
52. Manson JE, Nathan DM, Krolewski AS, Stampfer MJ, Willett WC, Hennekens CH. A prospective
study of exercise and incidence of diabetes among US male physicians. JAMA 1992; 268(1):63–67.
53. Manson JE, Rimm EB, Stampfer MJ et al. Physical activity and incidence of non-insulin-dependent
diabetes mellitus in women. Lancet 1991; 338(8770):774–778.
54. Helmrich SP, Ragland DR, Leung RW, Paffenbarger RS, Jr. Physical activity and reduced occurrence
of non-insulin-dependent diabetes mellitus. N Engl J Med 1991; 325(3):147–152.
260 Kordonouri et al.
55. Hu FB, Sigal RJ, Rich-Edwards JW et al. Walking compared with vigorous physical activity and risk
of type 2 diabetes in women: a prospective study. JAMA 1999; 282(15):1433–1439.
56. Knowler WC, Barrett-Connor E, Fowler SE et al. Reduction in the incidence of type 2 diabetes with
lifestyle intervention or metformin. N Engl J Med 2002; 346(6):393–403.
57. Lindstrom J, Louheranta A, Mannelin M et al. The Finnish Diabetes Prevention Study (DPS): lifestyle
intervention and 3-year results on diet and physical activity. Diabetes Care 2003; 26(12):3230–3236.
58. Lindstrom J, Ilanne-Parikka P, Peltonen M et al. Sustained reduction in the incidence of type 2 diabetes by life-
style intervention: follow-up of the Finnish Diabetes Prevention Study. Lancet 2006; 368(9548):1673–1679.
59. ADA. American Dietetic Association Care Manual; 2008.
60. Garg A, Bantle JP, Henry RR et al. Effects of varying carbohydrate content of diet in patients with non-
insulin-dependent diabetes mellitus. JAMA 1994; 271(18):1421–1428.
61. Chandalia M, Garg A, Lutjohann D, von BK, Grundy SM, Brinkley LJ. Beneficial effects of high
dietary fiber intake in patients with type 2 diabetes mellitus. N Engl J Med 2000; 342(19):1392–1398.
62. Schaefer EJ. Lipoproteins, nutrition, and heart disease. Am J Clin Nutr 2002; 75(2):191–212.
63. Ornish D, Scherwitz LW, Billings JH et al. Intensive lifestyle changes for reversal of coronary heart
disease. JAMA 1998; 280(23):2001–2007.
64. Elmer PJ, Obarzanek E, Vollmer WM et al. Effects of comprehensive lifestyle modification on diet,
weight, physical fitness, and blood pressure control: 18-month results of a randomized trial. Ann Intern
Med 2006; 144(7):485–495.
65. Lau SH, editor. Nutrition. In: Medica Management of Non-Insulin-Dependent (Type II) Diabetes. 3 ed.
Alexandria, VA: ADA; 1994, p. 45–67.
66. Franz MJ. Medical nutrition therapy. In: Davidson MB, editor. Diabetes mellitus Diagnosis and Treat-
ment. 4 ed. Philadelphia, PA: WB Saunders; 1998, p. 45–79.
67. Lada AT, Rudel LL. Dietary monounsaturated versus polyunsaturated fatty acids: which is really better
for protection from coronary heart disease? Curr Opin Lipidol 2003; 14(1):41–46.
68. West SG, Hecker KD, Mustad VA et al. Acute effects of monounsaturated fatty acids with and with-
out omega-3 fatty acids on vascular reactivity in individuals with type 2 diabetes. Diabetologia 2005;
48(1):113–122.
69. Institute of Medicine. Dietary Reference Intakes: Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cho-
lesterol, Protein and Amino Acids. Washington DC: Academies; 2002.
70. Albers AR, Krichavsky MZ, Balady GJ. Stress testing in patients with diabetes mellitus: diagnostic and
prognostic value. Circulation 2006; 113(4):583–592.
71. ADA. Standards of medical care in diabetes. Diabetes Care 2005; 28 Suppl 1:S4–S36.
72. Lau SH. Exercise. In: Lau SH, editor. Medical Management of Non-Insulin-Dependent(Type II)
Diabetes. 3 ed. Alexandria, VA: ADA; 1994, p. 36–39.
14 Mediterranean Diet in Disease
Prevention: Current Perspectives
Jessica Fargnoli, Yoon Kim,
and Christos S. Mantzoros
KEY POINTS
• Populations living around the Mediterranean Sea experience increased longevity and reduced
risk of cardiovascular diseases and cancers in relation to populations living in other regions
of the world.
• Much of this health benefit has been attributed to the traditional dietary patterns of the inhab-
itants of the Mediterranean basin.
• The traditional Mediterranean dietary pattern is often characterized by high consumption of
plant foods such as vegetables, fruits, legumes, and whole grains; use of olive oil as the pri-
mary source of fat; moderate intake of fish, poultry, dairy, and alcohol; and low consumption
of red meat.
• Results from ecological, case–control, and cohort studies have suggested that consumption of a
diet similar to a traditional Mediterranean dietary pattern may reduce the risk of chronic diseases
such as the metabolic syndrome, type 2 diabetes, cardiovascular disease, and many cancers.
• Present scientific knowledge suggests that this dietary pattern may have more health benefits
than other currently used diets for the prevention of several chronic diseases.
Key Words: Mediterranean diet, Metabolic syndrome, Diabetes, Cardiovascular disease,
Cancer
1. INTRODUCTION
The “Mediterranean Diet” has been the focus of countless books, weight loss pro-
grams, and research investigations, steadily rising in popularity since its benefits were
first noticed. In the 1950s, the scientific community began to observe that populations
in the Mediterranean basin were far less susceptible to chronic diseases, such as car-
diovascular disease (CVD), than populations in more westernized countries (1). These
findings were certainly not due to an advantage in medical care. In fact, at that time
socioeconomic indicators in many Mediterranean countries were lower when compared
with more westernized countries (2). What, then, was responsible for these health
From: Nutrition and Health: Nutrition and Metabolism
Edited by: C.S. Mantzoros, DOI: 10.1007/978-1-60327-453-1_14,
© Humana Press, a part of Springer Science + Business Media, LLC 2009
263
264 Fargnoli, Kim, and Mantzoros
benefits? The aspect of the Mediterranean lifestyle that the scientific community quickly
focused on was the diet these populations consumed. This was largely due to informa-
tion garnered from a groundbreaking cohort study undertaken by Ancel Keys. The Seven
Countries Study began in 1958 and collected information on diet, lifestyle, and chronic
disease in middle-aged men in the countries of Japan, Italy, Greece, the Netherlands,
Finland, Yugoslavia, and the United States. This ecologic study was the first study to
bring to light the mortality benefit enjoyed by the populations living in the Mediterra-
nean basin (1) by demonstrating that inhabitants of Greece and southern Italy were less
likely to develop cardiovascular disease compared with inhabitants of countries with a
more westernized diet. This health benefit was thus linked to foods that abounded in the
Mediterranean region at this time such as whole grains, legumes, a variety of fresh local
and wild vegetables, seasonal fruits, seafood and fish, nuts, yogurt, wine, and perhaps
most importantly, extra virgin olive oil.
2. WHAT CONSTITUTES A MEDITERRANEAN DIET?
Broadly defined, the Mediterranean Diet is the traditional dietary pattern of the popu-
lation living in the olive-growing regions of the Mediterranean basin in the late 1950s
and early 1960s. This may be misleading however, because there are many olive-growing
countries in the Mediterranean region, with variations in culture and dietary patterns
between them. This region spans southern Europe, northern Africa, and the Middle East,
but research has focused mainly on the diets in the European countries of Spain, Greece,
Italy, and France. However, dietary patterns are not uniform even among the European
countries. For instance, a traditional Greek Mediterranean diet may include total fat
intake of up to 40% of daily energy, depending on the region, while a traditional Ital-
ian Mediterranean diet is defined by a much lower total fat intake, less than 30% of
daily energy (3,4). The diet of Mediterranean Italy is characterized by higher intake
of complex carbohydrates, mostly due to pasta consumption, while the diet of Spain
is defined by a higher intake of fish (5). Though there is variation among dietary pat-
terns, the central characteristic of Mediterranean cuisine is high olive oil consumption.
A rich source of monounsaturated fat, olive oil has been widely studied for its health
benefits. In addition to its own beneficial properties, olive oil may encourage higher
consumption of vegetables and legumes. Since olive oil is the major source of fat in most
traditional Mediterranean cooking, the resulting diets are very low in saturated fat, as
low as 8% of daily energy intake in the areas where Keys first noticed the health benefit
(1). Likely as a result of its use of olive oil, the entire Mediterranean region has higher
ratios of monounsaturated fatty acid (MUFA) intake to saturated fatty acid (SFA) intake
than other regions of the world (5). Many have attributed the lower risk of CVD in the
Mediterranean region to this aspect of the diet. Furthermore, it appears that the percent-
age of total fat in the diet is not as significant as the ratio of poly and monounsaturated
fat to saturated and trans-fat for CVD prevention (6). Dietary recommendations in the
USA and elsewhere were strongly influenced by this discovery, and as saturated fat
was replaced with polyunsaturated fat over the next 25 years, CVD rates declined by
about 50% in the USA, the UK, and Australia (7). Emphasis has also been placed on the
increased consumption of vegetables and fish and the decreased consumption of meat in
the Mediterranean region. The area’s reduced cancer and CVD rates have been partially
attributed to the high intake of fruits and vegetables (8,9) and the low intake of red meat
Chapter 14 / Mediterranean Diet in Disease Prevention: Current Perspectives 265
(5,10). Moreover, diets high in fish and n-3 fatty acids have been shown to be beneficial
for the prevention of cardiovascular disease (10). Research increasingly points to the
Mediterranean dietary pattern as a possible explanation for the longevity of populations
living in this area; however, other aspects of the relaxed Mediterranean lifestyle such as
the after-lunch siesta and the presence of strong social networks cannot be ignored as
potential contributors to good health and long life (11).
3. DEFINING THE MEDITERRANEAN DIET
Initial public health efforts led to more research into the beneficial effects of the Med-
iterranean diet as a whole, and thus a need for a better definition of the dietary pattern
emerged. At the International Conference on the Diets of the Mediterranean in 1993, the
Mediterranean diet was defined as a dietary pattern composed of: abundant plant foods;
minimally processed, seasonally fresh, and locally grown foods; fresh fruits as the typi-
cal daily dessert with sweets based on nuts, olive oil, and concentrated sugars or honey
consumed during feast days; olive oil as the principal source of added fat; dairy products
(mainly cheese and yogurt) consumed in low to moderate amounts; fewer than four eggs
consumed per week; red meat consumed in low frequency amounts; and wine consumed
in low to moderate amounts generally with meals (12).
This definition was expanded upon in 1995 when a group of Harvard-led scientists
created a Mediterranean dietary pyramid (Fig. 1) (12) consisting of (a) daily consump-
tion: of nonrefined cereals and products (whole grain bread, pasta, brown rice, etc.),
vegetables (2–3 servings/day), fruits (6 servings/day), olive oil (as the main added lipid)
and dairy products (1–2 servings/day); (b) weekly consumption: of fish (4–5 servings/
week), poultry (3–4 servings/week), olives, pulses, and nuts (3 servings/week), potatoes,
eggs and sweets (3–4 servings/week); and (c) monthly consumption: of red meat and
meat products (4–5 servings/month). It is also characterized by moderate consumption
of wine (1–2 glasses/day) and high monounsaturated: saturated fat ratio (>2). Similar
recommendations are included in a Greek Column Food Guide, created to take the Greek
culture into account (13).
In addition, many Mediterranean diet scores have been developed for investigational
purposes. Trichopoulou et al. developed the Mediterranean Diet Score (MDS), which
measures individuals’ adherence to a traditional Greek-style Mediterranean diet pattern.
It is scored in terms of eight components: (1) high ratio of monounsaturated to satu-
rated fats; (2) moderate alcohol consumption; (3) high consumption of legumes; (4)
high consumption of cereals; (5) high consumption of fruits; (6) high consumption of
vegetables; (7) low consumption of meat and meat products; (8) low consumption
of milk and dairy products (14). Panagiotakos et al. also developed a diet score used to
measure subjects’ adherence to a Greek Mediterranean-type diet (15–17). The MedDi-
etScore is based on 11 components of the Mediterranean diet (nonrefined cereals, fruits,
vegetables, potatoes, legumes, olive oil, fish, red meat, poultry, full fat dairy products,
and alcohol) (18,19). For each component, an individual is assigned a score from 0 to
5 based on their level of consumption; however, red meat, poultry, and full fat dairy
products are scored on a reverse scale since they deviate from the Mediterranean diet.
These are added together to create a Mediterranean diet scale from 0 to 55, with the
highest score corresponding to the closest adherence to the dietary pattern. Alternatively,
the Mediterranean Adequacy Index (MAI) is associated with individuals’ adherence to
266 Fargnoli, Kim, and Mantzoros
Fig. 1. Mediterranean diet pyramid.
a traditional Italian-style Mediterranean dietary pattern (20). It uses as its reference the
diet of Nicotera, Italy, in the 1960s, which was one of the rural areas studied in Keys’
Seven Countries Study. The MAI is calculated by dividing the sum of the percentage of
total energy from typical Mediterranean food groups (bread, cereals, legumes, potatoes,
vegetables, fruit, fish, vegetable oils, and red wine) by the sum of the percentage of total
energy from nontypical Mediterranean food groups (milk, cheese, meat, eggs, animal fats
and margarines, cakes, pies, and cookies, and sugar) (21). Of the three, the MAI has not
been as widely studied. Several other measures of Mediterranean diet adherence exist
and have been used in investigations (22). Thus far, the scientific community has not
defined one universal Mediterranean diet pattern, which may have ramifications when
it comes to the generalizablility and comparability of investigational studies.
Chapter 14 / Mediterranean Diet in Disease Prevention: Current Perspectives 267
Unfortunately, as research has begun to uncover the benefits of a traditional Mediter-
ranean diet, the diet of the Mediterranean region has progressively become more western-
ized since the 1960s. For example, three of the rural Italian towns, which were part of
Keys’ Seven Countries Study, now seem to be following a diet much more similar to the
average Western diet than a traditional Mediterranean diet. When studied in the 1990s,
the inhabitants of Nicotera, Crevalcore, and Montegiorgio were consuming much higher
amounts of animal foods, cakes, cookies, and sweet beverages than at the commencement
of the Seven Countries Study (23,24). As obesity rises to epidemic proportions and the
dietary patterns of many cultures are increasingly westernized, research into the health
benefits of a traditional Mediterranean diet becomes ever more necessary. The following
chapter will discuss the current body of scientific evidence on the Mediterranean dietary
pattern as a whole and its implications for the prevention of chronic disease, as well
as the public health importance of further clinical research into the effects of this diet.
Though sample sizes vary and different definitions of the Mediterranean diet have been
implemented, the evidence consistently demonstrates the benefits of the Mediterranean
dietary pattern on the metabolic syndrome and type 2 diabetes, cardiovascular disease
and its risk factors, certain types of cancer, and overall mortality.
4. MEDITERRANEAN DIET AND CARDIOVASCULAR DISEASE
Attention was first drawn to the diet of the Mediterranean through anecdotal evidence
about the significantly decreased prevalence of cardiovascular disease (CVD) in the
region (25). The Seven Countries Study went on to demonstrate the reduced risk of
CVD in the Mediterranean region, particularly in Crete, Greece (1). This led to further
research into the cardio-protective effects of a diet high in unsaturated fat and low in
saturated fat, as previously discussed. Similarly, other areas of the Mediterranean have
also been shown to have cardiac benefits as well. For example, studies of middle-aged
men in Finland, the Netherlands, and Italy have demonstrated that death rates from
coronary heart disease are much lower in Italy (26).
Cross-sectional associations between Mediterranean diet and CVD risk factors
have also been studied. A higher Mediterranean Diet Score has been associated
with reduction in blood pressure (27 ) and an inverse relationship has been found
between increased MedDietScore and hypercholesterolemia ( 28) .
In general, case–control studies have confirmed and expanded upon links between CVD
risk and the Mediterranean diet seen in population-based and cross-sectional research.
A number of case-control studies on the Mediterranean diet have found positive effects
on cardiovascular disease and cardiovascular risk factors including lipid profile, blood
pressure, BMI, and inflammatory markers. The multi-center case-control CARDIO2000
study has shown inverse associations between adherence to a Mediterranean-type diet and
risk of cardiovascular disease (29–33) and more specifically risk of developing nonfatal
acute coronary syndromes. Participants were recruited from all parts of Greece and 848
hospitalized patients with a first event of an acute coronary syndrome were enrolled and
compared with 1,078 people without any evidence of cardiovascular disease. Among
a sample of 661 patients with a first event of myocardial infarction or unstable angina
and 661 matched controls, adherence to a Mediterranean-type diet was associated with
a 16% reduction in risk of developing acute coronary syndromes, even when controlling
for exercise, smoking status, and various other cardiovascular risk factors (29). Adherence
268 Fargnoli, Kim, and Mantzoros
to the diet was also associated with reduced risk of diabetes mellitus and hypertension.
Various substudies of the CARDIO2000 have found relationships between the Mediter-
ranean diet and CVD among high-risk groups. Hypercholesterolemic patients following
a Mediterranean-type diet in conjunction with statin treatment experienced an additional
reduction in CVD risk of 43% (30). In addition, CVD risk was lowered by 7–17% among
controlled and uncontrolled hypertensive patients with a high adherence to a Mediterra-
nean-type diet (31). With the addition of moderate leisure-time physical activity, risk of
CVD was reduced even further, by 11–25% (32). Results from the CARDIO2000 were
also promising for patients with the metabolic syndrome. Adoption of the Mediterranean
diet by these subjects in this subgroup was associated with a 35% decline in risk for
an acute coronary event, after adjusting for various potential confounders (33). Results
from the CARDIO2000 suggest that consuming a traditional Mediterranean diet coul